Lamp adjusting method and device, storage medium, electronic equipment and lamp

Abstract

The invention discloses a lamp adjusting method and device, a storage medium, electronic equipment and a lamp. The method comprises the following steps: determining an illumination mode of a lamp; according to the illumination mode, determining an on-site visual color preference degree and a live scene color preference degree, the on-site visual color preference degree being used for indicating a color preference degree of an illumination light source generated by a lamp in a real environment, and the live scene color preference degree being used for indicating a live scene color preference degree; the live broadcast scene color preference degree is used for indicating the color preference degree of an illumination light source generated by the lamp in the live broadcast scene; determining a target parameter value of a target spectrum parameter of the lamp based on the on-site visual color preference degree and the live scene color preference degree; and adjusting the lamp based on the target parameter value. According to the invention, the technical problems of small lamp adjustment range and poor lamp adjustment effect caused by incomplete consideration factors during lamp adjustment in the prior art are solved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent lighting, and in particular to a lamp adjustment method, device, storage medium, electronic equipment and lamp. Background Art

[0002] At present, the public's interest and love for live streaming is gradually deepening. Therefore, how to scientifically and reasonably adjust the lamps, adjust and set the lighting source of the lamps to make the live broadcast picture fuller and more vivid, and enhance the audience's viewing experience, has become a common challenge faced by scholars in the field of lighting and beauty lamp manufacturers. How to adjust the lamps and set parameters to better adapt to the needs of various lamp usage scenarios has become an urgent problem to be solved. However, the relevant technology does not consider all factors when performing such lamp adjustment and parameter setting, resulting in a small lamp adjustment range and poor lamp adjustment effect.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] Embodiments of the present invention provide a lamp adjustment method, device, storage medium, electronic device and lamp, so as to at least solve the technical problem in the related art that factors are not fully considered when adjusting the lamp, resulting in a small lamp adjustment range and poor lamp adjustment effect.

[0005] According to one aspect of an embodiment of the present invention, there is provided a lamp adjustment method, comprising: determining a lighting mode of the lamp; determining a live visual color preference and a live scene color preference according to the lighting mode, wherein the live visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a live scene; determining a target parameter value of a target spectral parameter of the lamp based on the live visual color preference and the live scene color preference; and adjusting the lamp based on the target parameter value.

[0006] According to another aspect of an embodiment of the present invention, there is also provided a lamp adjustment method, comprising: obtaining a plurality of groups of spectral parameter values ​​for the lamp, wherein each group of spectral parameter values ​​includes parameter values ​​of a plurality of spectral parameters; obtaining on-site visual color preference and live scene color preference corresponding to the plurality of groups of spectral parameter values, wherein the on-site visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a live scene; based on the on-site visual color preference and live scene color preference corresponding to the plurality of groups of spectral parameter values, and the lighting mode of the lamp, determining a target group parameter value from the plurality of groups of spectral parameter values, wherein the target group parameter value includes the target parameter values ​​of the plurality of spectral parameters; and adjusting the lamp according to the target group parameter value.

[0007] According to another aspect of an embodiment of the present invention, a lamp adjustment device is also provided, including: a lighting mode determination module, used to determine the lighting mode of the lamp; a color preference determination module, used to determine the on-site visual color preference and the live scene color preference according to the lighting mode, wherein the on-site visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a live scene; a first parameter determination module, used to determine the target parameter value of the target spectral parameter of the lamp based on the on-site visual color preference and the live scene color preference; and a first adjustment module, used to adjust the lamp based on the target parameter value.

[0008] According to another aspect of an embodiment of the present invention, there is provided another lamp adjustment device, comprising: a parameter acquisition module, for acquiring multiple groups of spectral parameter values ​​of the lamp, wherein each group of spectral parameter values ​​includes parameter values ​​of multiple spectral parameters; a color preference acquisition module, for acquiring on-site visual color preference and live scene color preference corresponding to the multiple groups of spectral parameter values, wherein the on-site visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a live scene; a second parameter determination module, for determining a target group parameter value from the multiple groups of spectral parameter values ​​based on the on-site visual color preference and live scene color preference corresponding to the multiple groups of spectral parameter values, and the lighting mode of the lamp, wherein the target group parameter value includes the target parameter values ​​of the multiple spectral parameters; a second adjustment module, for adjusting the lamp according to the target group parameter value.

[0009] According to another aspect of an embodiment of the present invention, a non-volatile storage medium is provided, wherein the non-volatile storage medium stores a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing any one of the lamp adjustment methods.

[0010] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement any one of the lamp adjustment methods.

[0011] In an embodiment of the present invention, a lighting mode of a lamp is determined; based on the lighting mode, a live visual color preference and a live scene color preference are determined, wherein the live visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a live scene; based on the live visual color preference and the live scene color preference, a target parameter value of a target spectral parameter of the lamp is determined; based on the target parameter value, the lamp is adjusted, thereby achieving the purpose of combining the lighting mode, selecting spectral parameters and adjusting the lamp from both the live visual and live scene aspects, thereby achieving the technical effect of expanding the adjustment range of the lamp and improving the adjustment effect of the lamp, thereby solving the technical problem in the related art that the factors are not fully considered when adjusting the lamp, resulting in a small adjustment range and poor adjustment effect of the lamp. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0013] Figure 1 is a flow chart of a lamp adjustment method according to an embodiment of the present invention;

[0014] Figure 2 is a flow chart of an optional lamp adjustment method according to an embodiment of the present invention;

[0015] Figure 3 is a flow chart of another lamp adjustment method according to an embodiment of the present invention;

[0016] Figure 4 is a flow chart of another optional lamp adjustment method according to an embodiment of the present invention;

[0017] Figure 5is a schematic diagram of a lamp adjustment device according to an embodiment of the present invention;

[0018] Figure 6 is a schematic diagram of another lamp adjustment device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0020] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0021] First, to facilitate understanding of the embodiments of the present invention, some terms or nouns involved in the present invention are explained below:

[0022] Lab is a color space model, also referred to as "Lab color space" or "Lab color space", which is used to create a uniform color space that matches the color perceived by the human eye. The Lab color space consists of three coordinate axes: the L axis represents lightness, from 0 (black) to 100 (white); the a axis represents the color change from green to red; the b axis represents the color change from blue to yellow. When describing skin color, the Lab value of the skin usually refers to the three values ​​of L*, a*, and b* corresponding to a certain skin area in this color space. These values ​​can fully reflect the brightness, redness, and yellowness of the skin, and are often used in many fields such as cosmetics development, skin testing, and color matching to describe and analyze the characteristics of skin color in a scientific way.

[0023] In today's era of social media, live streaming, as a new and popular field, has been favored by more and more users. The popularity of live streaming platforms has also driven the development of related industries. Among them, lighting, as one of the most important elements in the live streaming environment, plays a vital role in the live streaming effect.

[0024] In live broadcasting scenarios, the importance of lighting parameters cannot be ignored. Lighting affects the quality of the picture, the degree of color reproduction, and the visual experience of the audience. First of all, good lighting can make the picture clearer and more realistic, ensuring that the details of the anchor and the object being photographed can be clearly presented. Secondly, proper lighting can improve the degree of color reproduction, make the picture fuller and more vivid, and enhance the audience's viewing experience. Finally, reasonable lighting settings can also create atmosphere and emotions, and increase the artistic sense and appeal of the live broadcast content.

[0025] Therefore, in the live broadcast scene, the setting of lighting parameters needs to fully consider the characteristics and needs of the live broadcast content, and reasonably set the position, angle and intensity of the light source to achieve the best effect. At the same time, it is also necessary to select suitable lamps and light color temperatures according to different live broadcast themes and styles, so as to improve the visual quality and viewing value of the live broadcast. In summary, the importance of lighting parameters in the live broadcast scene cannot be ignored. It is directly related to the quality of the live broadcast effect and plays a vital role in improving the quality of the live broadcast and attracting viewers.

[0026] At present, the public's interest and love for live streaming is gradually deepening. Therefore, how to scientifically and reasonably adjust the lamps and set the lighting source to make the live broadcast picture fuller and more vivid and enhance the audience's viewing experience has become a challenge faced by scholars in the field of lighting and beauty lamp manufacturers. Due to the particularity of different groups of people, unique lighting methods are needed to avoid appreciation defects and aesthetic fatigue. With the continuous in-depth research on beauty lamps, the evaluation of lamp lighting quality is particularly important. Color temperature, illumination and preference are important contents in the multi-dimensional evaluation of lamp lighting quality.

[0027] However, in the related art, incomplete factors are considered when performing such lamp adjustment and parameter setting, resulting in a small lamp adjustment range and poor lamp adjustment effect.

[0028] In response to the above problems, an embodiment of the present invention provides an embodiment of a method for adjusting a lamp. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0029] Figure 1 is a flow chart of a lamp adjustment method according to an embodiment of the present invention. Figure 1As shown, the method comprises the following steps:

[0030] Step S102, determining the lighting mode of the lamp;

[0031] Optionally, the lamp can be, but is not limited to, an LED lamp. Compared with traditional lamps, the light source of lamps based on LED technology has many advantages such as high efficiency, low radiation, and long life. The adjustable light color LED technology creates a clearer and more realistic immersive experience for the live broadcast image expression. The lighting mode can include, but is not limited to, live broadcast mode, performance mode, outdoor mode, and normal mode.

[0032] In step S102 of the present application, the selection of the lighting mode can adjust the light source parameters in a personalized manner according to the specific usage scenario and needs. For example, the live broadcast mode pays more attention to the color temperature and color rendering of the light source to ensure the skin color of the anchor and the visual effect of the live broadcast screen; the performance mode needs to emphasize the richness and dynamic effects of colors to match the atmosphere of the stage performance; and the outdoor mode pays more attention to the naturalness of the light source to simulate the daylight effect. Therefore, the selection of the lighting mode directly affects the direction and focus of the subsequent spectral parameter adjustment.

[0033] Step S104, determining the on-site visual color preference and the live scene color preference according to the lighting mode, wherein the on-site visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in the real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in the live scene;

[0034] In step S104 of the present application, the spectral parameters are finely adjusted according to different lighting modes to meet the visual and aesthetic requirements of specific scenes. For example, in the live broadcast mode, the lamps will pay more attention to improving the color reproduction of the live broadcast picture and the aesthetics of the anchor's skin, while in the live mode, it may focus more on creating a comfortable and natural viewing environment. By calculating and determining the color preference in different scenes, the lamps can automatically adjust to the color performance that the user is most satisfied with, thereby significantly improving the user experience. Regardless of the lighting mode, the lamps can provide the best color effects and enhance the atmosphere and visual enjoyment of the environment. The color preference of the live vision and live broadcast scenes can be based on a large amount of experimental data and user feedback, as well as combined with other embodiments in the present application, which can guide the lamps to make scientific parameter adjustments. The above method is more comprehensive than the adjustment based on a single factor, and can take into account the complex influence of the light source on the environmental color perception.

[0035] In an optional embodiment, the on-site visual color preference and the live scene color preference are determined according to the lighting mode, including: obtaining a preset target color preference, wherein the target color preference is used to indicate the comprehensive color preference for the lighting source generated by the lamp; determining, according to the lighting mode, a first weight coefficient corresponding to the on-site visual color preference and a second weight coefficient corresponding to the live scene color preference; determining a target proportional coefficient between the on-site visual color preference and the live scene color preference; and determining the on-site visual color preference and the live scene color preference based on the target color preference, the first weight coefficient, the second weight coefficient and the target proportional coefficient.

[0036] Optionally, by setting the target color preference and weight coefficient, the color preference of the user in different scenes can be personalized. The preferences in different lighting modes are different. By adjusting the first weight coefficient and the second weight coefficient, it can be ensured that the light source characteristics of the lamp are closer to the needs of the user in the current mode. The introduction of the target proportional coefficient allows the relative importance of the live visual color preference and the live scene color preference to be dynamically adjusted in different lighting modes. For example, in the live mode, the live scene color preference may be given a higher weight, while in the reading mode, the live visual color preference may be more important. This dynamic adjustment can improve the flexibility and scene adaptability of the lamp adjustment. The target color preference, as the user's expectation of the comprehensive color performance of the light source, can guide the target of the lamp adjustment. By combining with the live visual and live scene color preferences, it can be ensured that the light source adjustment not only takes into account the preferences of a single scene, but also takes into account the optimization of the overall color performance to achieve the best visual experience. By accurately matching the lighting mode and user preferences, the lamp can provide a more comfortable and beautiful lighting effect, which can significantly improve the user experience in terms of visual appeal in the live scene and the naturalness of the color in the live environment.

[0037] It should be noted that the determination of the weight coefficient and the target ratio coefficient can be based on experimental data and user feedback. The above method can ensure that the lamp adjustment is based on empirical data, closer to actual needs, and provide scientific and reasonable light source configuration. obj , On-site visual color preference S pre , live scene color preference S′ pre There is the following relationship between them: Sp obj =c1*S pre + c 2*S′ pre , where c1 is the first weight coefficient, c2 is the second weight coefficient, and the target color preference Sp obj When the target ratio coefficient is determined, the on-site visual color preference S can be obtained by the following method: pre, live scene color preference S′ pre :S pre =Sp obj *(c1+c2 / k Sp ); S′ pre =Sp obj *(c1*k Sp +c2), where k Sp =S pre / S′ pre =4.2±0.5,Sp obj The value range of can be 4.5~25.0.

[0038] Optionally, in different lighting modes, different combinations of the first weight coefficient c1 and the second weight coefficient c2 correspond, for example, in live broadcast mode, c1:c2=0.2:0.8; in performance mode, c1:c2=0.6:0.4; in outdoor mode, c1:c2=0.8:0.2; in normal mode, c1:c2=0.5:0.5.

[0039] In an optional embodiment, determining a target ratio coefficient between a live visual color preference and a live scene color preference includes: obtaining a scene preference, wherein the scene preference is used to indicate a degree of preference for a live visual scene and a live scene; and determining a target ratio coefficient between a live visual color preference and a live scene color preference based on the scene preference.

[0040] Optionally, the scene preference can reflect the user's preference for the on-site visual scene and the live broadcast scene, so that the adjustment of the lamps is closer to the actual needs of the user. For example, if the user prefers the live broadcast scene, the scene preference will indicate a higher live scene color preference weight, and vice versa. The change in scene preference allows the lamp to dynamically adjust the ratio between the on-site visual color preference and the live broadcast scene color preference to ensure the best lighting experience in any case. This dynamic adjustment mechanism enables the lamps to flexibly adapt to changes in user preferences and different usage scenarios. By accurately matching user preferences, lamps can provide more comfortable and beautiful lighting effects, whether it is the natural color restoration of on-site vision or the beauty lighting of live broadcast scenes, which can effectively improve the user experience. The introduction of scene preference enables the lamps to automatically adjust the target ratio coefficient based on user input or intelligent environmental perception, thereby realizing the intelligent and automated lighting adjustment.

[0041] Step S106, determining a target parameter value of a target spectral parameter of the lamp based on the on-site visual color preference and the live scene color preference;

[0042] In step S106 of the present application, by quantifying the color preferences under the scene vision and live broadcast scenes, the specific preferences of users for the color of light sources in different scenes can be accurately understood, thereby ensuring that these preferences can be directly considered and matched when adjusting the lamps, so that the light sources are closer to user needs. The scene vision color preference and the live broadcast scene color preference represent the performance of the light source in two different environments. Based on these two preferences, the optimal target spectral parameters can be calculated to optimize the color output of the lamp and improve the visual comfort and aesthetics of the light source. By dynamically monitoring and adjusting the preference, the lamp can seamlessly switch between different lighting modes, automatically adapt to the changes in the scene or live broadcast scene, and ensure that the light source is always in the best state. For example, when the user switches from live broadcast mode to reading mode, the lamp can quickly adjust the spectral parameters to adapt to the new lighting needs. Through the comprehensive consideration of the scene vision color preference and the live broadcast scene color preference, the determination of the target parameter value is more comprehensive, which not only pays attention to the intuitive performance of color, but also takes into account the comprehensive impact of color on the scene atmosphere and live broadcast content, thereby achieving higher quality lighting adjustment.

[0043] Optionally, the target spectrum parameters may include, but are not limited to, correlated color temperature CCT, chromaticity deviation Duv value, illuminance E, color rendering index Ra, and whiteness index Sneutral of the light source.

[0044] In an optional embodiment, based on the on-site visual color preference and the live scene color preference, the target parameter value of the target spectral parameter of the lamp is determined, including: based on the on-site visual color preference and the live scene color preference, a spectral parameter prediction model is used to obtain the target parameter value of the target spectral parameter, wherein the spectral parameter prediction model pre-learns the correlation between the target spectral parameter and the on-site visual color preference and the live scene color preference.

[0045] Optionally, the spectral parameter prediction model can accurately predict and configure the most suitable spectral parameter values ​​based on the user's on-site visual preferences and live scene requirements by learning and understanding the correlation between the target spectral parameters and the on-site visual color preferences and the live scene color preferences. This means that the lamp can provide a highly personalized lighting experience based on the user's preferences in different scenes. The use of the spectral parameter prediction model makes the lamp adjustment process more intelligent. The model can automatically analyze the preference of the current scene, determine the target parameter value without the user manually adjusting multiple complex parameters, realize the automatic optimization configuration of the light source, and enhance the adaptability of the lamp to different scenes. Through model prediction, the lamp can quickly respond to changes in user preferences, whether pursuing natural and realistic color presentation in on-site vision or seeking beautification effects in live scenes, and can provide the best lighting effects and significantly improve user satisfaction. The spectral parameter prediction model can respond to user preferences and scene changes in real time, dynamically adjust the target parameter value, and ensure that the lamp can provide the most suitable lighting effect at any time and in any scene, thereby enhancing the continuity and consistency of the user experience. In addition, by integrating the spectral parameter prediction model, lamps can achieve more complex and intelligent light source adjustment. It is no longer a simple color temperature or illumination adjustment, but a comprehensive consideration of the impact of light source characteristics on on-site vision and color preference of live broadcast scenes, thereby improving the overall intelligence level of lamps.

[0046] Optionally, the prediction model of spectral parameters can be obtained based on a large amount of experimental data and user preference learning. Specifically, the spectral parameter prediction model can be based on multiple sets of data, with on-site visual color preference and live scene color preference as independent variables, and the parameter value of the target spectral parameter as the dependent variable, obtained by model fitting, wherein each set of data includes a parameter value of a target parameter, and the corresponding on-site visual color preference and live scene color preference. Among them, multiple sets of data can be obtained through experiments combined with the calculation method of other embodiments.

[0047] In an optional embodiment, in the case where the spectral parameter prediction model includes a first spectral parameter prediction model and a second spectral parameter prediction model, the spectral parameter prediction model is used based on the on-site visual color preference and the live scene color preference to obtain a target parameter value of the target spectral parameter, including: obtaining a scene preference type; in the case where the scene preference type is a first preference type, based on the on-site visual color preference and the live scene color preference, the first spectral parameter prediction model is used to obtain the target parameter value, wherein the first preference type is used to indicate that the degree of preference for the on-site visual scene is greater than the degree of preference for the live scene; or in the case where the scene preference type is a second preference type, based on the on-site visual color preference and the live scene color preference, the second spectral parameter prediction model is used to obtain the target parameter value, wherein the second preference type is used to indicate that the degree of preference for the on-site visual scene is less than the degree of preference for the live scene.

[0048] Optionally, by distinguishing the scene preference types, the lamp adjustment can more accurately match the user's preference in a specific scene. If the user prefers the live visual scene, the first spectral parameter prediction model will predict the parameters dominated by the live visual color preference; conversely, when the live scene preference is heavier, the second spectral parameter prediction model will consider the influence of the live scene color preference more. This mechanism allows the lamp to select the most appropriate spectral parameter prediction model based on the preference type entered by the user or through intelligent perception of the environment. Not only can the user operate, but it also makes the lamp adjustment decision more intelligent and efficient. Selecting models according to different preference types can avoid unnecessary light source parameter adjustments and reduce energy waste. For example, in the live visual preference scene, the lamp may choose a more natural light, while in the live preference scene, it may be more inclined to use a light source that beautifies the color. Whether it is a live visual scene or a live scene, by selecting an appropriate prediction model to adjust the light source, users can be sure to get a consistent and high-level lighting experience, and can respond quickly and achieve satisfactory results regardless of how the preference changes.

[0049] Optionally, the target scaling factor k Sp =4.2±0.5, it can be set to Sp When ≥4.2, the scene preference type is the first preference type, mainly offline scenes; Sp <4.2, the scene preference type is the second preference type, mainly based on the live scene. For example, taking the correlated color temperature CCT as the target spectrum parameter, calculate the correlated color temperature CCT of the target spectrum (maximum spectrum preference influence parameter, other spectrum parameters are set to fixed values, Ra = 90, Duv = 0.000, Ex = 300lx, Sneutral = 7.50); ​​if k SpWhen ≥4.2, offline scenes are mainly used; according to the first spectral parameter prediction model, S pre =-0.7508*(CCT / 1000)^2+8.6716*(CCT / 1000), based on the above model, the parameter value of the target spectral parameter correlated color temperature CCT can be calculated, and there are 2 CCT values ​​to determine the target parameter value. Sp <4.2, the live broadcast scene is the main one; according to the second spectral parameter prediction model, S ′ pre =-0.2688*(CCT / 1000)^2+2.9422*(CCT / 1000)-1.9486, the parameter value of the target spectral parameter correlated color temperature CCT is calculated, and the quadratic equation has two CCT values ​​to determine the target parameter value.

[0050] In an optional embodiment, the lamp is adjusted based on the target parameter value, including: detecting whether the target parameter value is within a predetermined parameter range; if the target parameter value is not within the predetermined parameter range, optimizing the target parameter value, and adjusting the lamp based on the optimized target parameter value.

[0051] Optionally, by detecting whether the target parameter value is within the predetermined parameter range, it can be ensured that the target parameter set by the user does not exceed the physical or technical limitations of the lamp, thereby avoiding the situation where the lamp cannot respond or malfunctions due to unreasonable user settings. When the target parameter value exceeds the predetermined range, optimization can intelligently adjust the target parameter to make it as close to the user's needs as possible while keeping it within the actual capabilities of the lamp. This optimization can be based on the maximum output capacity, color temperature range, safe operating range, etc. of the lamp. By limiting the parameter range and optimizing the parameter values ​​that exceed the range, system instability or safety issues such as overheating and circuit overload that may be caused by setting unreasonable parameters can be effectively avoided. Through the above optimization mechanism, the lamp can better adapt to changes in different scenarios and user needs. Even if the target parameter settings are inappropriate, it can adjust the lighting effect closest to the user's expectations, thereby enhancing the adaptability and flexibility of the lamp.

[0052] Optionally, when there are multiple target parameter values ​​output by the spectral parameter prediction model that are within the predetermined parameter range, the parameter value closest to the upper limit of the predetermined parameter range among the multiple target parameter values ​​is used as the final target parameter value to adjust the lamp. Still taking the correlated color temperature CCT as the target spectral parameter as an example, for the aforementioned CCT calculation results (i.e., the two calculated CCT values), check whether they are within the predetermined parameter range (e.g., 3000-7000K). If one of them is within the range, the parameter value within the range is used as the target parameter value; if both are within the range, the parameter value closer to the upper limit of the range (i.e., 7000K) is used as the final target parameter value to adjust the lamp. If both are not within the predetermined parameter range, the target proportional coefficient k is adjusted. Sp , or adjust the target color preference Sp obj The target parameter value is re-determined in this way.

[0053] Step S108: adjusting the lamp based on the target parameter value.

[0054] In step S108 of the present application, the target parameter value includes the user's preference for the color of the lamp in a specific scene (such as a live broadcast or live broadcast). By adjusting the lamp based on these spectral parameter values, it can be ensured that the light source output by the lamp meets the personalized needs of the user, thereby providing the user with a more satisfactory and comfortable lighting experience. In a live broadcast or live environment, the characteristics of the light source directly affect the image quality and the audience's visual perception. The adjustment of the target parameter value based on the target spectral parameter can optimize the key spectral parameters of the light source, such as color temperature, illumination, and color rendering index, to achieve the best visual effect and improve the quality of the live broadcast picture or the viewing experience of the scene. The lamp can flexibly switch between a variety of lighting modes according to different target parameter values, which can ensure that the most suitable light source can be provided in a variety of different lighting modes, and enhance the adaptability of the lamp to different scenes.

[0055] In an optional embodiment, the lamp has multiple spectral parameters, and the multiple spectral parameters include a target spectral parameter and other spectral parameters, wherein the parameter values ​​of the other spectral parameters are preset values.

[0056] Optionally, by allowing specific spectral parameters (such as color temperature and illuminance) to be adjusted, personalized control of lighting effects can be achieved, while keeping other parameters (such as color rendering index, light source whiteness, etc.) at preset values ​​to ensure the consistency and stability of the lamps in basic lighting quality standards. Focusing on key spectral parameters (target spectral parameters), such as color temperature or illuminance, allows lamps to meet core lighting needs more effectively without having to make complex adjustments to all parameters, simplifying the user operation process and improving adjustment efficiency. Being able to intuitively adjust target spectral parameters based on scene preferences without having to worry about complex adjustments to the entire spectral configuration, this simplified process improves the convenience of user operation and thus enhances user satisfaction with the lamps. Fixing certain parameters at preset values ​​can reduce the complexity of system adjustment, reduce the risk of technical failures caused by excessive adjustments, and enhance the stability and reliability of the lamp lighting system.

[0057] In an optional embodiment, the lamp is adjusted based on the target parameter value, including: when it is detected that the parameter values ​​of other spectral parameters of the lamp need to be optimized, based on the new on-site visual color preference and the new live scene color preference, obtaining the optimized parameter values ​​of the other spectral parameters, wherein the other spectral parameters are spectral parameters of the multiple spectral parameters of the lamp except the target spectral parameters; the lamp is adjusted based on the target parameter value and the optimized parameter value.

[0058] Optionally, by optimizing multiple spectral parameters, including but not limited to target spectral parameters and other spectral parameters, the lamp can more comprehensively meet the lighting needs of users in specific scenarios, such as the coordinated adjustment of color temperature and illumination to obtain the best color rendering effect. When it is detected that other spectral parameters of the lamp need to be optimized, the parameter value is automatically adjusted according to the new on-site visual color preference and the live scene color preference. When setting the target parameters, the user may not consider all parameters that may affect the lighting effect. By intelligently optimizing other spectral parameters, the lighting system can be closer to the real needs of users and improve the overall satisfaction of the lighting experience. There is a complex interaction between spectral parameters. By optimizing other parameters, the coordination between parameters can be ensured to avoid undesirable changes in other parameters that may be caused by the adjustment of a single parameter, such as keeping the color rendering index within a reasonable range when adjusting the color temperature to ensure the authenticity and saturation of the picture color.

[0059] Optionally, still taking the target spectral parameter as color temperature CCT as an example, when the parameter value of the target spectral parameter is determined, other spectral parameters (including Duv, Ra, Sneutral, and illuminance Ex in addition to color temperature CCT) are further optimized. Specifically, based on the initially set target color preference, the on-site visual color preference and the live scene color preference are further adjusted to obtain new on-site visual color preference and new live scene color preference (S pre 2 and S ′ pre 2), and then obtain the new target color preference (i.e., the new target preference). pre 2 and S ′ pre 2. Use a single factor influencing factor method or a double factor influencing factor method to adjust the parameter values ​​of other spectral parameters by recalculating and comparing the target color preference on the basis of changing the parameter values ​​of other spectral parameters (one or two). The specific calculation method of the target color preference is the same as that in other embodiments of the present application, and will not be repeated here. The single factor influencing factor method refers to the case of changing one other spectral parameter, and the double factor influencing factor method refers to the case of changing two other spectral parameters at the same time. Specifically as follows: When the other spectral parameter that needs to update the parameter value is illumination, set the spectral parameter value (illuminance 100~800lx, interval 100lx, other parameters unchanged, CCT is CCTobj, Ra=90, Duv=0.00, Sneutral=7.50), and by changing the illumination value, obtain a set of target color preference Spre_Exi obtained under the influence of illumination. The new target preference is compared with Spre_Exi. If it is within the range, the optimal illumination value Ex and the optimized spectral parameters (i.e., the target color temperature CCTobj) are obtained by the insertion method. Specifically:

[0060] When the other spectral parameter that needs to be updated is Duv, set the spectral parameter value (Duv = -0.010 ~ 0.010, interval 0.002, other parameters remain unchanged, CCT is CCTobj, Ra = 90, Ex = 300lx, Sneutral = 7.50), and obtain a set of target color preference Spre_Duvi under the influence of Duv by changing the Duv value. The new target preference is compared with Spre_Duvi, and the optimal illumination value Duv value and optimized spectral parameters are obtained by insertion method within the range.

[0061] Or, when the other spectral parameter that needs to be updated is Ra, set the spectral parameter value (Ra = 80.0 ~ 100.0, interval 5.0, other parameters remain unchanged, CCT is CCTobj, Duv = 0.000, Ex = 300lx, Sneutral = 7.50), and by changing the Ra value, obtain a set of on-site visual color preferences and live scene color preferences Spre_Rai under the influence of Ra. The new target preference is compared with Spre_Rai, and within its range, the optimal illumination value Ra value and optimized spectral parameters are obtained by insertion method.

[0062] Or, when the other spectral parameter that needs to be updated is Sneutral, set the spectral parameter value (Sneutral = 6.0-8.0, interval 0.5, other parameters remain unchanged, CCT is CCTobj, Ra = 90, Duv = 0.000, Ex = 300lx), and obtain a set of target color preference Spre_Sneutrali under the influence of Sneutral by changing the Sneutral value. The new target preference is compared with Spre_SneutralRai, and within its range, the optimal illuminance value Sneutral value and the optimized spectral parameter are obtained by insertion method.

[0063] When the other spectral parameters that need to be updated are illumination + Duv, set the spectral parameter values ​​(illuminance = 100-800lx, interval 100lx; Duv = -0.010-0.010, interval 0.002, other parameters remain unchanged, CCT is CCTobj, Ra = 90, Sneutral = 7.50), and by changing the values ​​of illumination and Duv at the same time, a set of on-site visual color preferences and live scene color preferences Spre_Exi_Duvj obtained under the dual influence of illumination and Duv is obtained. The new target preference is compared with Spre_Exi_Duvj. If it is within its range, the optimal illumination value Ex, Duv value and optimized spectral parameters are obtained by insertion method.

[0064] Or, when the other spectral parameters that need to be updated are Ra+Duv, set the spectral parameter values ​​(Ra=80.0~100.0, interval 5.0; Duv=-0.010~0.010, interval 0.002, other parameters remain unchanged, CCT is CCTobj, Ex=300lx, Sneutral=7.50), and by changing the values ​​of Ra and Duv at the same time, a set of on-site visual color preferences and live scene color preferences Spre_Rai_Duvj under the dual influence of Ra and Duv is obtained. The new target preference is compared with Spre_Rai_Duvj, and within its range, the optimal Ra value, illuminance value Duv value and optimized spectral parameters are obtained by insertion method.

[0065] Or, when the other spectral parameters that need to be updated are Ra+Sneutral, set the spectral parameter values ​​(Ra=80.0-100.0, interval 5.0; Sneutral=6.0-8.0, interval 0.5, other parameters remain unchanged, CCT is CCTobj, Duv=0.000, Sneutral=7.50), and by changing the values ​​of Ra and Sneutral at the same time, a set of on-site visual color preference and live scene color preference Spre_Rai_Sneutralj obtained under the dual influence of Ra and Sneutral is obtained. The new target preference is compared with Spre_Rai_Sneutralj, and within its range, the optimal illumination value Ra value, Sneutral value and optimized spectral parameters are obtained by insertion method.

[0066] If the optimized spectral parameter values ​​are not calculated, the coefficients use the preset spectral parameter values ​​{5700K, 3001x, Ra=90, Duv=0.000, Sneutral=7.50}.

[0067] Through the above steps S102 to S108, the purpose of combining the lighting mode, selecting spectral parameters and adjusting the lamps from the two aspects of on-site vision and live broadcast scene can be achieved, thereby achieving the technical effect of expanding the adjustment range of the lamps and improving the adjustment effect of the lamps, and further solving the technical problem in the related technology that the factors are not fully considered when adjusting the lamps, resulting in a small adjustment range of the lamps and poor adjustment effect of the lamps.

[0068] Based on the above embodiments and optional embodiments, the present invention proposes an optional implementation mode: Figure 2 is a flow chart of an optional lamp adjustment method according to an embodiment of the present invention, such as Figure 2 As shown, the method includes:

[0069] S21, selecting a lighting mode, wherein the lighting mode is any one of the following: live mode, performance mode, outdoor mode, and normal mode;

[0070] S22, determining a first weight coefficient c1 and a second weight coefficient c2, in live broadcast mode, c1:c2=0.2:0.8; in performance mode, c1:c2=0.6:0.4; in outdoor mode, c1:c2=0.8:0.2; in normal mode, c1:c2=0.5:0.5;

[0071] S23, setting target color preference Sp obj , Sp obj The range is (4.5~25.0);

[0072] S24, calculating the on-site visual color preference Spre and the live scene color preference S′ pre ;

[0073] Take S pre With S′ pre The ratio of k Sp =S pre / S′ pre =4.2±0.5, k Sp The specific value of (i.e., k_Sp) can be determined based on the scene preference, with a default value of 4.2. The above parameters satisfy the following relationship:

[0074] Sp obj =c1*S pre +c2*S′ pre ;

[0075] S pre =Sp obj *(c1+c2 / k Sp );

[0076] S′ pre =Sp obj *(c1*k Sp +c2);

[0077] S25, taking the correlated color temperature CCT as the target spectrum parameter, calculating the correlated color temperature CCT of the target spectrum (maximum spectrum preference influence parameter, other spectrum parameters are set to fixed values, Ra=90, Duv=0.000, Ex=3001x, Sneutral=7.50);

[0078] If k Sp When ≥4.2, offline scenarios are mainly used:

[0079] According to the first spectral parameter prediction model, S pre=-0.7508*(CCT / 1000)^2+8.6716*(CCT / 1000). Based on the above model, the parameter value of the target spectral parameter correlated color temperature CCT can be calculated. There are two CCT values. If both CCT values ​​in the CCT calculation result are not within 3000-7000K, ignore the value; if both CCR values ​​are within 3000-7000K, take the value closer to 5700K as the target parameter value, that is, the target color temperature CCTobj; if there is no valid value, that is, both CCR values ​​are not within 3000-7000K, then adjust k Sp Get the value or adjust the target color preference Sp obj The size of is recalculated (starting from step S23).

[0080] If k Sp <4.2, mainly live broadcast scenes:

[0081] According to the second spectral parameter prediction model, S′ pre =-0.2688*(CCT / 1000)^2+2.9422*(CCT / 1000)-1.9486, the parameter value of the target spectral parameter correlated color temperature CCT is calculated. The quadratic equation has two CCT values. If both CCT values ​​in the CCT result are not within 3000~7000K, ignore the value; if both CCT values ​​are within 3000~7000K, take the value closer to 5700K as the target parameter value, that is, the target color temperature CCTobj; if there is no valid value, that is, both CCR values ​​are not within 3000~7000K, then adjust k Sp Get the value or adjust the target color preference Sp obj The size of is recalculated (starting from step S23).

[0082] Finally, the target parameter values ​​of the target spectral parameters {CCTobj, Ex=3001x, Ra=90, Duv=0.000, Sneutral=7.5} are calculated.

[0083] S26, further optimizing other spectral parameters (including Duv, Ra, Sneutral, and illuminance Ex in addition to color temperature CCT).

[0084] On the basis of the initially set target color preference, the on-site visual color preference and the live scene color preference are further adjusted to obtain a new on-site visual color preference and a new live scene color preference (S pre 2 and S′ pre 2), and then obtain the new target color preference (i.e., the new target preference). pre 2 and S′ pre2. Use a single factor influencing factor method or a double factor influencing factor method to adjust the parameter values ​​of other spectral parameters by recalculating and comparing the target color preference based on changing the parameter values ​​of other spectral parameters (one or two). The specific calculation method of the target color preference is the same as that in other embodiments of the present application and will not be repeated here. The single factor influencing factor method refers to the case of changing one other spectral parameter, and the double factor influencing factor method refers to the case of changing two other spectral parameters at the same time. The details are as follows:

[0085] When the other spectral parameter that needs to be updated is illumination, set the spectral parameter value (illuminance 100-8001x, interval 1001x, other parameters unchanged, CCT is CCTobj, Ra=90, Duv=0.00, Sneutral=7.50), and obtain a set of target color preference Spre_Exi under the influence of illumination by changing the illumination value. The new target preference is compared with Spre_Exi, and the optimal illumination value Ex and optimized spectral parameters (i.e., target color temperature CCTobj) are obtained by insertion method if they are within the range.

[0086] Or, when the other spectral parameter that needs to be updated is Duv, set the spectral parameter value (Duv = -0.010 to 0.010, interval 0.002, other parameters remain unchanged, CCT is CCTobj, Ra = 90, Ex = 300lx, Sneutral = 7.50), and obtain a set of target color preference Spre_Duvi under the influence of Duv by changing the Duv value. The new target preference is compared with Spre_Duvi, and the optimal illuminance value Duv value and optimized spectral parameters are obtained by insertion method within the range.

[0087] Or, when the other spectral parameter that needs to be updated is Ra, set the spectral parameter value (Ra = 80.0 ~ 100.0, interval 5.0, other parameters remain unchanged, CCT is CCTobj, Duv = 0.000, Ex = 300lx, Sneutral = 7.50), and by changing the Ra value, obtain a set of on-site visual color preferences and live scene color preferences Spre_Rai under the influence of Ra. The new target preference is compared with Spre_Rai, and within its range, the optimal illumination value Ra value and optimized spectral parameters are obtained by insertion method.

[0088] Or, when the other spectral parameter that needs to be updated is Sneutral, set the spectral parameter value (Sneutral = 6.0-8.0, interval 0.5, other parameters remain unchanged, CCT is CCTobj, Ra = 90, Duv = 0.000, Ex = 300lx), and obtain a set of target color preference Spre_Sneutrali under the influence of Sneutral by changing the Sneutral value. The new target preference is compared with Spre_SneutralRai, and within its range, the optimal illuminance value Sneutral value and the optimized spectral parameter are obtained by insertion method.

[0089] Or, when the other spectral parameters that need to be updated are illumination + Duv, set the spectral parameter values ​​(illuminance = 100-800lx, interval 100lx; Duv = -0.010-0.010, interval 0.002, other parameters remain unchanged, CCT is CCTobj, Ra = 90, Sneutral = 7.50), and by changing the values ​​of illumination and Duv at the same time, a set of on-site visual color preferences and live scene color preferences Spre_Exi_Duvj obtained under the dual influence of illumination and Duv is obtained. The new target preference is compared with Spre_Exi_Duvj, and within its range, the optimal illumination value Ex, Duv value and optimized spectral parameters are obtained by insertion method.

[0090] Or, when the other spectral parameters that need to be updated are Ra+Duv, set the spectral parameter values ​​(Ra=80.0~100.0, interval 5.0; Duv=-0.010~0.010, interval 0.002, other parameters remain unchanged, CCT is CCTobj, Ex=300lx, Sneutral=7.50), and by changing the values ​​of Ra and Duv at the same time, a set of on-site visual color preferences and live scene color preferences Spre_Rai_Duvj under the dual influence of Ra and Duv is obtained. The new target preference is compared with Spre_Rai_Duvj, and within its range, the optimal Ra value, illuminance value Duv value and optimized spectral parameters are obtained by insertion method.

[0091] Or, when the other spectral parameters that need to be updated are Ra+Sneutral, (Ra=80.0-100.0, interval 5.0; Sneutral=6.0-8.0, interval 0.5, other parameters remain unchanged, CCT is CCTobj, Duv=0.000, Sneutral=7.50), by changing the values ​​of Ra and Sneutral at the same time, a set of on-site visual color preference and live scene color preference Spre_Rai_Sneutralj under the dual influence of Ra and Sneutral is obtained. The new target preference is compared with Spre_Rai_Sneutralj, and within its range, the optimal illumination value Ra value, Sneutral value and optimized spectral parameters are obtained by insertion method.

[0092] If the optimized spectral parameter values ​​are not calculated, the coefficients use the preset spectral parameter values ​​{5700K, 300lx, Ra=90, Duv=0.000, Sneutral=7.50}.

[0093] According to an embodiment of the present invention, another method embodiment of lamp adjustment is provided. Figure 3 is a flow chart of a lamp adjustment method according to an embodiment of the present invention. Figure 3 As shown, the method comprises the following steps:

[0094] Step S302, obtaining multiple groups of spectral parameter values ​​of the lamp, wherein each group of spectral parameter values ​​includes parameter values ​​of multiple spectral parameters;

[0095] In step S302 of the present application, by collecting multiple sets of spectral parameter values, the lamp adjustment system can cover a wide range of lighting effects, including combinations of parameters such as different color temperatures, illumination, color rendering index, Duv value, and whiteness of light sources. This diversity provides users with a rich range of choices that can meet different scenes and personalized lighting needs. Each set of spectral parameter values ​​contains multiple spectral parameters, which means that the impact of various parameters on lighting quality can be fully evaluated and understood. Compared with focusing only on a single parameter (such as color temperature or illumination), the above method can more accurately predict and evaluate the lighting effects under different parameter combinations to ensure the optimization of overall lighting quality. The acquisition of multiple sets of spectral parameter values ​​provides users with more flexibility in choice. Users can freely choose the most suitable spectral parameter combination based on their preferences and current scene requirements based on the visual color preference of the scene and the color preference of the live scene. With a data basis of multiple spectral parameter values, the lamp adjustment system can make intelligent decisions based on complex algorithms and models. The best group can be automatically selected from multiple sets of parameter values, or dynamically optimized, to achieve the most ideal lighting effect based on user preferences and scene requirements. Different scenes and users may have unique requirements for spectral parameters. The acquisition of multiple sets of spectral parameter values ​​enables the system to adapt to a variety of different situations. Whether it is on-site vision or live broadcast scenes, it can provide customized lighting solutions and enhance the versatility and adaptability of the lamps.

[0096] Step S304, obtaining the on-site visual color preference and the live scene color preference corresponding to the multiple groups of spectral parameter values, wherein the on-site visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in the real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in the live scene;

[0097] In step S304 of the present application, the on-site visual color preference and the live scene color preference represent people's subjective preferences for the color of the lighting source in different application scenarios. By calculating these preferences, it is possible to more accurately understand the lighting needs of users in different environments and achieve more personalized and user-friendly lighting effects. The on-site visual color preference focuses on the visual experience in the real environment, while the live scene color preference focuses on optimizing the visual presentation during live broadcasts. This distinction makes the adjustment of lamps more scene-based, and can optimize lighting parameters more accurately for specific application scenarios (such as indoor reading, live broadcast rooms, outdoor live broadcasts, etc.). Each set of spectral parameter values ​​corresponds to a specific on-site visual color preference and live scene color preference. This means that it is possible to evaluate the impact of different parameter combinations on the lighting effect, including multiple dimensions such as color temperature, illumination, color rendering index, Duv value, light source whiteness, etc., so as to select the best combination among multiple sets of spectral parameter values. By calculating the on-site visual and live scene color preferences, it is possible to ensure that the most satisfactory lighting effect can be provided in any scenario (whether on-site or live), enhance the user's visual comfort and the quality of the live broadcast effect, thereby improving the overall user experience.

[0098] Optionally, when multiple spectral parameters include at least correlated color temperature (CCT), chromaticity deviation value (Duv), illuminance E and other parameters, before executing step S304, a preliminary judgment and screening of the spectral parameter values ​​can also be performed to ensure that the selected parameter values ​​are within the applicable range of the lamp. Specifically, measure the spectral power distribution of the light source to be used in the lamp; calculate the correlated color temperature (CCT) of the light source to be used, unit: Kelvin (K); determine whether the correlated color temperature CCT of the light source to be used is within the correlated color temperature range used in this embodiment, that is, determine whether CCT1≤CCT≤CCT2 is established, if not, this embodiment is not applicable, if so, proceed to the subsequent judgment process; further calculate the chromaticity deviation Duv value of the light source to be used; determine whether the Duv value of the light source to be used is within the Duv range applicable to this embodiment, that is, determine whether Duv1≤Duv≤Duv2 is established, if not, this embodiment is not applicable, if so, proceed to the next judgment process; further determine the lighting The illuminance E of the light source at the observed person, unit: lux (lx), wherein the observed person is used to indicate the object illuminated by the light source to be used; judging whether the illuminance E of the light source to be used at the observed person is within the illuminance range used in the present embodiment, that is, judging whether E1≤E≤E2 is established; if not, the present embodiment is not applicable; if so, proceeding to the next judgment process; further measuring the Lab value of the observed person's skin color space; judging whether the observed person's skin color classification angle ITA° is within the applicable range of the present embodiment of the present invention, that is, judging whether ITA1°≤ITA°≤ITA2° is established; if not, the present embodiment is not applicable; if so, executing the relevant operations of step S304.

[0099] In an optional embodiment, when multiple spectral parameters include at least color temperature, chromaticity deviation value, and illuminance, obtaining the on-site visual color preference and live scene color preference corresponding to multiple groups of spectral parameter values ​​respectively includes: determining the on-site visual related color temperature influence factor and the live scene related color temperature influence factor based on the color temperature in any group of parameter values, wherein the on-site visual related color temperature influence factor is used to evaluate the influence of the light source color temperature on the on-site visual effect, and the live scene related color temperature influence factor is used to evaluate the influence of the light source color temperature on the live picture effect; determining the on-site visual illuminance influence factor based on the illuminance in any group of parameter values, wherein, The on-site visual illuminance influence factor is used to evaluate the impact of illuminance on on-site visual effects; the on-site visual color preference corresponding to any set of parameter values ​​is obtained based on the on-site visual related color temperature influence factor, the on-site visual illuminance influence factor and the chromaticity deviation value in any set of parameter values; the live scene color preference corresponding to any set of parameter values ​​is obtained based on the live scene related color temperature influence factor and the chromaticity deviation value in any set of parameter values; the on-site visual color preference and live scene color preference corresponding to any set of parameter values ​​are obtained by obtaining the on-site visual color preference and live scene color preference corresponding to any set of parameter values, thereby obtaining the on-site visual color preference and live scene color preference corresponding to multiple sets of spectral parameter values.

[0100] Optionally, by quantifying parameters such as color temperature, chromaticity deviation value, and illuminance as influencing factors in the scene vision and live broadcast scenes, the impact of these parameters on the visual effect can be more accurately evaluated, thereby obtaining a more scientific preference evaluation result, so that the final adjusted light source is closer to the actual needs of the user. The scene vision-related color temperature influencing factor and the live broadcast scene-related color temperature influencing factor simultaneously consider the specific role of the light source color temperature in different scenes. When selecting the adjustment parameters, the matching degree between the light source color temperature and the scene requirements can be fully considered to improve the pertinence and effect of the adjustment. The introduction of the scene vision illuminance influencing factor can quantitatively analyze the impact of illuminance on the scene visual experience. In practical applications, this analysis can help optimize the illuminance level during adjustment to adapt to the lighting requirements at different times and in different environments and improve visual comfort. The chromaticity deviation value (Duv) is a parameter that measures the difference between the chromaticity of the light source and the ideal chromaticity, which is crucial to the color reproduction of the live broadcast screen. By comprehensively considering the color temperature, illuminance, and Duv value, the color performance of the light source can be more comprehensively evaluated, the color accuracy of the live broadcast screen can be ensured, and the viewing experience of the audience can be improved.

[0101] Optionally, the scene visual correlated color temperature influence factor S can be determined based on, but not limited to, the color temperature CCT in any set of parameter values ​​by the following method: CCT .

[0102] S CCT=p1+p2*cos(w0*CCT)+p3*sin(w0*CCT)

[0103] p1=-8.6078×10 5

[0104] p2=8.6078×10 5

[0105] p3=-1.981×10 3

[0106] w0=-3.9854×10 -7

[0107] Optionally, the on-site visual illumination influence factor E can be determined based on, but not limited to, the illumination E in any set of parameter values ​​by the following method: CCT .

[0108] E CCT =p1*E p2

[0109] p1=0.5183

[0110] p2=0.1311

[0111] Optionally, it can be but not limited to the light source spectral power distribution, light source chromaticity deviation value Duv, on-site visual correlation color temperature influence factor S CCT , on-site visual illumination influence factor E CCT , the on-site visual color preference S of any set of parameter values ​​can be obtained by the following method pre :

[0112] S pre =S CCT *E CCT *(p1*Duv+p2*R a +p3*S neutral +p4)

[0113] p1=4.08242×10 2

[0114] p2=1.3×10 -2

[0115] p3=3.083

[0116] p4=-1.426×10 1

[0117] Wherein, Duv is the Duv value of the light source to be used in the lamp, R a is the color rendering index of the light source to be used, S neutralIt is an index of the whiteness of the light source to be used, and can be calculated from the spectral power distribution of the light source to be used.

[0118] The color rendering index R of the light source to be used can be obtained by, but is not limited to, the following method: a :

[0119]

[0120] R i =p1+p2*ΔE i

[0121] p1=1.000×10 2

[0122] p2=-4.600

[0123] Among them, R i is the color rendering index of each CIE test color, ΔE i The color difference between each test color under the light source to be used and the standard light source can be obtained from the spectral reflectance of the light source to be used and the spectral reflectance of the CIE test color.

[0124] The whiteness index Sneutral of the light source to be used can be calculated in the following manner, but is not limited to, in a preset uniform color space:

[0125] S neutral =x*e y

[0126] y=-0.5[n1(u′-n3) 2 +n2(v′-n4) 2 +2n5(u′-n3)(v′-n4)]

[0127] x=8.1, n1=1494.9, n2=981.9, n3=0.2081, n4=0.4596, n5=-722.2

[0128] Among them, u ′ and v ′ is the chromaticity coordinate of the light source to be used in the preset uniform color space.

[0129] Optionally, the color temperature influence factor S of the live scene can be determined by, but is not limited to, the color temperature CCT in any set of parameter values ​​in the following manner: ′ CCT .

[0130]

[0131] p1=1.0072

[0132] p2=5.4837×10 3

[0133] p3=4.4725×10 3

[0134] Wherein, CCT is the correlated color temperature of the light source to be used.

[0135] Optionally, it can be based on but limited to the spectral power distribution of the light source to be used, the light source Duv, and the live scene related color temperature influence factor S ′ CCT , light source whiteness S neutral , calculate the color preference S of the live scene for any set of parameter values ​​by the following method ′ pre .

[0136] S ′ pre =S ′ CCT *(p1+p2*Duv+p3*S neutral +p4*Duv 2 +p5*Duv*S neutral )

[0137] p1=-1.72173×10 -1

[0138] p2=5.645×10 -1

[0139] p3=8.334×10 -1

[0140] p4=-3.010×10 -3

[0141] p5=-1.380×10 -2

[0142] Step S306, determining a target group parameter value from the multiple groups of spectral parameter values ​​based on the on-site visual color preference, the live scene color preference, and the lighting mode of the lamp corresponding to the multiple groups of spectral parameter values, wherein the target group parameter value includes the target parameter values ​​of the multiple spectral parameters respectively;

[0143] In step S306 of the present application, by analyzing the preferences under different spectral parameter combinations, the lamps can automatically select the most matching spectral parameter settings according to the user's personalized needs and preferences, thereby improving the lighting experience and meeting the user's aesthetic needs in different scenarios. The on-site visual color preference and the live scene color preference can reflect the evaluation of the lighting effect in the real environment and the live scene, respectively. Combined with the lighting mode, it can intelligently identify the current scene, and then select the most suitable combination for the current scene from multiple groups of spectral parameter values ​​to ensure that the lamps can provide the best lighting effect in various environments. The lamp adjustment is based on the user's on-site and live scene preferences, which can more accurately match the user's visual preferences and avoid inappropriate lighting effects, such as color distortion, excessive or low illumination, etc., thereby significantly improving the user's visual experience and satisfaction in real environments and live scenes.

[0144] In an optional embodiment, based on the on-site visual color preferences, live scene color preferences, and lighting modes of the lamps and lanterns corresponding to the multiple groups of spectral parameter values, target group parameter values ​​are determined from the multiple groups of spectral parameter values, including: based on the lighting mode, determining a first weight coefficient corresponding to the on-site visual color preferences, and a second weight coefficient corresponding to the live scene color preferences; based on the on-site visual color preferences, live scene color preferences, the first weight coefficient, and the second weight coefficient corresponding to the multiple groups of spectral parameter values, determining the target color preferences corresponding to the multiple groups of spectral parameter values, wherein the target color preference is used to indicate the comprehensive color preference degree for the lighting source generated by the lamps and lanterns; based on the target color preferences corresponding to the multiple groups of spectral parameter values, determining the target group parameter values ​​from the multiple groups of spectral parameter values.

[0145] Optionally, by assigning different weights to the on-site visual color preference and the live scene color preference, the lighting adjustment system can adapt to different usage scenarios more flexibly. For example, in the live broadcast mode, the weight of the live scene color preference may be higher to ensure the best color performance of the live screen; while in the reading or indoor working mode, the weight of the on-site visual color preference may be higher to create a more comfortable visual environment. The setting of the weight coefficient allows the user to adjust the priority of the on-site visual and live scene according to personal preferences, so as to obtain a more personalized lighting experience. If the user is more concerned about the visual effect during the live broadcast, the weight of the live scene color preference can be increased manually or through system settings, and vice versa. The target color preference is the weighted average of the on-site visual color preference and the live scene color preference, thereby ensuring that when selecting the target group parameter value, not only the preference of a single scene is considered, but the comprehensive preference of the two scenes is fully considered, so as to find a balance between various lighting needs. By calculating the weighted preference, the real needs of the user can be identified more accurately, avoiding the deviation that may be caused by a single preference evaluation. This comprehensive evaluation based on weighted coefficients makes the adjustment of lamps more precise and can achieve the lighting effect expected by users. The target group parameter values ​​determined based on the weights are used to optimize the lighting effect, so that lamps can provide high-quality lighting experience in different lighting modes, thus significantly enhancing user satisfaction and comfort.

[0146] Optionally, the first weight coefficient c1 and the second weight coefficient c2 satisfy the following condition: c1+c2=1, and the ratio of the two can be determined according to the actual lighting mode requirements. For example, if the lighting mode is set to live mode, c1:c2=1:4; if the lighting mode is set to performance mode, c1:c2=3:2; if the lighting mode is set to outdoor mode, c1:c2=4:1. In actual use, by customizing the coefficient relationship between c1 and c2, the predicted emphasis of the lamp color preference is adjusted to adapt to different usage scenarios.

[0147] Optionally, it can be based on but not limited to the visual color preference S of the scene pre , live scene color preference S ′ pre , and the first weight coefficient c1 and the second weight coefficient c2 determined according to the lighting mode, the target color preference of any set of parameter values ​​is obtained in the following manner:

[0148] S p =c1*S pre +c2*S ′ pre

[0149] Among them, S p Represents the target color preference for any set of parameter values.

[0150] Optionally, a group of spectral parameter values ​​corresponding to the largest target color preference among the multiple groups of spectral parameter values ​​may be determined as the target group parameter values.

[0151] Step S308: adjusting the lamps according to the target group parameter values.

[0152] In step S308 of the present application, the target group parameter value is determined based on the user's preference for the color of the lighting source in different scenes, which means that the lamp adjustment can customize the lighting according to personal preferences, providing a more personalized, comfortable and beautiful lighting experience. By adjusting the lamp to the target group parameter value, the lamp can achieve the best color reproduction and visual effects in the live broadcast scene and the real environment, ensuring that the color saturation and details of the anchor and the observed object are optimized under different light sources, improving the attractiveness of the live broadcast picture and the comfort of the on-site vision.

[0153] Through the above steps S302 to S308, the purpose of combining the lighting mode, selecting spectral parameters and adjusting the lamps from the two aspects of on-site vision and live broadcast scene can be achieved, thereby achieving the technical effect of expanding the adjustment range of the lamps and improving the adjustment effect of the lamps, and further solving the technical problem in the related technology that the factors are not fully considered when adjusting the lamps, resulting in a small adjustment range of the lamps and poor adjustment effect of the lamps.

[0154] Based on the above embodiments and optional embodiments, the present invention proposes another optional implementation mode: Figure 4 is a flow chart of an optional lamp adjustment method according to an embodiment of the present invention, such as Figure 4 As shown, the method includes:

[0155] S41, measuring the spectral power distribution of the light source to be used of the lamp, for example, the spectral power distribution of the light source to be used may adopt 380nm-700nm band information;

[0156] S42, calculating the correlated color temperature (CCT) of the light source to be used, in Kelvin (K), for example, the correlated color temperature CCT1 = 3000k, CCT2 = 7000k;

[0157] S43, determining whether the correlated color temperature CCT of the light source to be used is within the correlated color temperature range used in this embodiment, that is, determining whether CCT1≤CCT≤CCT2 is established. If not, this embodiment is not applicable. If established, proceed to the next step.

[0158] S44, calculating the chromaticity deviation Duv value of the light source to be used, for example, the chromaticity deviation values ​​Duv1 = -0.01, Duv2 = 0.01;

[0159] S45, determining whether the Duv value of the light source to be used is within the Duv range applicable to this embodiment, that is, determining whether Duv1≤Duv≤Duv2 is established. If not, this embodiment is not applicable. If established, proceed to the next step.

[0160] S46, measuring the illuminance E of the illumination light source at the observed person, in units of lux (lx), where the observed person is used to indicate the object illuminated by the light source to be used, for example, illuminance E1 = 100 lx, E2 = 800 lx;

[0161] S47, determining whether the illumination E of the light source to be used at the observed person is within the illumination range used in this embodiment, that is, determining whether E1≤E≤E2 is established. If not, this embodiment is not applicable. If established, proceed to the next step.

[0162] S48, measuring the Lab value of the observed person's skin color space, for example, the observed person's features are measured using a Lab uniform color space, and the observed person's skin color classification angles ITA1°=10°, ITA2°=55°;

[0163] S49, determining whether the observed person's skin color classification angle ITA° is within the applicable range of this embodiment, that is, determining whether ITA1°≤ITA°≤ITA2° holds. If not, this embodiment is not applicable. If so, proceed to the next step.

[0164] S410, calculating the scene visual correlated color temperature influence factor S according to the correlated color temperature information of the light source to be used in step S42 CCT The specific calculation method is the same as above and will not be repeated here.

[0165] S411, calculating the scene visual illumination influence factor E according to the illumination information of the light source to be used at the observed person in step S46 CCT The specific calculation method is the same as above and will not be repeated here.

[0166] S412, according to the light source spectral power distribution, light source chromaticity deviation value Duv, and scene visual correlation color temperature influence factor S obtained in steps S41, S44, S410, and S411 CCT , on-site visual illumination influence factor E CCT , and calculate the scene visual color preference S pre The specific calculation method is the same as above and will not be repeated here.

[0167] S413, calculating the correlated color temperature impact factor S of the live scene according to the correlated color temperature information of the light source to be used in step S42 ′ CCT The specific calculation method is the same as above and will not be repeated here.

[0168] S414, based on the spectral power distribution of the light source to be used in steps S41, S44, S412, and S413, the light source Duv, and the live scene-related color temperature influencing factor S ′ CCT , light source whiteness S neutral , calculate the color preference S of the live scene ′ pre The specific calculation method is the same as above and will not be repeated here.

[0169] S415, the on-site visual color preference S obtained in step S412 and step S414 is pre , live scene color preference S ′ pre , according to the lighting mode used, input the beauty light color preference prediction model (i.e. S p =c1*S pre +c2*S ′ pre ), the target color preference under different combinations of spectral parameter values ​​is obtained, and then the color preference prediction of the beauty light for live broadcast is realized under the multi-factor interaction of light source correlated color temperature, Duv, illuminance and light source whiteness.

[0170] S416, determining a group of spectral parameter values ​​with the greatest target color preference among the multiple different spectral parameter value combinations as target group parameter values; and adjusting the lamp based on the target group parameter values.

[0171] As an optional embodiment, a lamp adjustment method based on the correlated color temperature, Duv, illuminance, and whiteness of the light source emitted by the lamp is provided, and the optimal parameter value (such as the target parameter value) is selected based on the prediction result to dim the lamp. The correlated color temperature, Duv, and illuminance indicators of the light source to be predicted are relied upon, and a combination of on-site vision and live scene preference prediction and estimation is used as a means to achieve a comprehensive and accurate prediction and evaluation of the target color preference of the light source to be predicted under the action of multi-spectral parameters of light source color temperature, Duv, illuminance, and whiteness of the light source, thereby achieving accurate dimming of the lamp.

[0172] This embodiment uses 14 LED light sources with different correlated color temperatures as the light sources to be used: including correlated color temperature values ​​of 4000K, 4500K, 5000K, and 6000K, Duv values ​​of -0.01, -0.005, 0, 0.005, and 0.01, and skin color illuminance values ​​of 140lx, 210lx, 306lx, 386lx, and 460lx; a model with ITA°=30° is used as the observed person; the results of psychophysical experiments are used as the basis for model verification, and the accuracy of the lamp adjustment method based on the correlated color temperature, Duv, illuminance, and whiteness of the light source proposed in this embodiment is explained. It should be noted that this embodiment is not limited to the above-mentioned light sources and model skin colors, and this embodiment is also applicable to other LED light sources or other skin colors. The specific steps are as follows:

[0173] S1, measuring the spectral power distribution of the light source to be used, and calculating the correlated color temperature CCT and Duv value of the light source;

[0174] In the embodiment, an illuminometer is used to measure the light source to be used, and the spectral power distribution information of 380nm-780nm is obtained, and the correlated color temperature and Duv value of the light source to be used are calculated accordingly. The correlated color temperatures of the light sources to be used in the embodiment are 3000K, 4000K, 4500K, 5000K, and 6000K, and the Duv of the light sources are -0.01, -0.005, 0, 0.005, and 0.01, respectively.

[0175] S2, judging whether the correlated color temperature CCT and Duv value of the light source to be used are within the applicable range of the present embodiment, that is, judging whether CCT1≤CCT≤CCT2 and Duv1≤Duv≤Duv2 are established. If not, the present embodiment is not applicable. If established, proceed to the next step. In the embodiment, the correlated color temperature CCT1=3000K, CCT2=7000K, Duv1=-0.01, and Duv2=0.01.

[0176] S3, measuring the illuminance of the light source to be used at the observer. In the embodiment, an illuminance meter is used to measure the light source to be used, and the illuminances to be used in the embodiment are measured as follows: illuminance values ​​140lx, 210lx, 306lx, 386lx, and 460lx.

[0177] S4, determine whether the illuminance E of the light source to be used at the observer is within the applicable range of this embodiment, that is, determine whether E1≤E≤E2 is established. If not, this embodiment is not applicable. If yes, proceed to the next step. In the embodiment, E1=100lx, E1=800lx.

[0178] S5, measuring the skin color characteristics of the model and expressing them using the uniform color space Lab;

[0179] In the embodiment, the skin type of the common skin color of a specific population is used as a screening standard for the user population, and a spectrophotometer is used to obtain the color characteristics of the skin, and the color characteristics are expressed by a uniform color space Lab.

[0180] S6, calculate the skin classification angle ITA°;

[0181] In the embodiment, the skin classification angle ITA° is calculated by the measured Lab value.

[0182] S7, determine whether the skin color ITA° of the user group is within the ITA° range applicable to this embodiment, that is, determine whether ITA1°≤ITA°≤ITA2° is established. If not, this embodiment is not applicable. If established, proceed to the next step. In the embodiment, ITA1°=10°, ITA2°=55°.

[0183] S8, based on the correlated color temperature CCT, Duv, and illuminance information of the light source to be used measured and calculated in steps S1 and S3, calculate the visual color preference S of the scene pre , live scene color preference S ′ pre .

[0184] S9, the on-site visual color preference S obtained in step S8 is pre , live scene color preference S ′ pre , according to the lighting mode used, input the beauty light color preference prediction model (i.e. S p =c1*S pre +c2*S ′ pre ), the predicted values ​​of the target color preference under different combinations of spectral parameter values ​​are obtained, and then the color preference prediction of the beauty light under the multi-factor interaction of light source correlated color temperature, Duv value, illuminance, color rendering index and light source whiteness is realized.

[0185] S10, determining a group of spectral parameter values ​​with the greatest target color preference among a plurality of different spectral parameter value combinations as target group parameter values; and adjusting the lamp based on the target group parameter values.

[0186] In order to further verify the technical advantages of the method of this embodiment in the prediction of target color preference and lamp adjustment, a psychophysical experiment is used to calculate the PEARSON correlation coefficient between the observer's preference for the model's skin color obtained by the psychophysical experiment and the predicted value of the target color preference in step S8 by the method of correlation coefficient R. The specific implementation is: using the above 15 types of light sources to be used as experimental light sources, and taking the model with skin color angle ITA°=30° as the observed, a psychophysical preference evaluation experiment is carried out, and the specific experimental method is as follows:

[0187] 1) The experiment was conducted in a dark room. A gray background cloth was placed in the experimental area. The above model was used as the observed person. During the experiment, the model sat in front of the gray background cloth to simulate the actual usage scenario of the network anchor. At the same time, other light sources were turned off during the experiment to avoid interference. Two intelligent LED light sources were set on both sides to illuminate the model to generate the designated experimental light source. The observer can move freely in the specified experimental area, so as to comprehensively and carefully observe the skin color of the model under the light source.

[0188] 2) During the experiment, the experimenter will change the experimental light sources with different parameters in the specified order. The observer needs to record the evaluation of the model's skin color preference in each experimental scene in the experimental record sheet according to the evaluation rules specified in the experiment. The evaluation rules are as follows:

[0189] The seven-level evaluation is adopted, with -3 points for "very dislike" and 3 points for "very like", and the larger the number, the higher the degree of preference. After the observer observes the model's skin color for a period of time, he can make a corresponding score. At the same time, other experimenters will continue to remind the observer to pay attention to the model's skin color from multiple angles as much as possible, so as to obtain a comprehensive evaluation.

[0190] 3) A total of 30 observers were selected for the experiment, all of whom had normal vision and were on average 18-30 years old. Before each experiment, the experimenter would orally introduce the experimental situation. During the experiment, the observers observed the model's skin color under the corresponding light source and made a preference evaluation, and then closed their eyes until the experimenter changed the next experimental light source. The observers observed again for a period of time and made a preference evaluation, and repeated this step until the last set of experimental scenes. A total of 15 sets of experimental scenes.

[0191] 4) After the experiment, the preference evaluation scores of all observers for the model's skin color were counted to calculate the PEARSON correlation coefficient between the subjective evaluation value and the target color preference prediction value constructed in this embodiment. The experimental results are shown in Table 1 below, where a larger value indicates a higher target color preference score under the light source.

[0192] Table 1

[0193]

[0194]

[0195] Through the above psychophysical experiment, the subjective evaluation values ​​of the model's skin color preference under different light sources by different observers can be obtained, and the PEARSON correlation coefficient between the subjective evaluation value and the predicted value of the target color preference constructed in this embodiment can be further calculated, as shown in the following Table 2. The results show that the correlation coefficient values ​​between the subjective evaluation value and the model estimation value in this embodiment are all above 0.90, proving that this embodiment has extremely high accuracy in predicting the target color preference based on the light source correlated color temperature, Duv, skin color illuminance, and light source whiteness, and further proving that the method of this embodiment has a strong technical advantage in predicting the color preference of the beauty light.

[0196] Table 2

[0197] PEARSON correlation coefficient CCT group preference 0.9441 Duv group preference 0.9304 Illumination group preference 0.9423

[0198] This embodiment proposes a method for predicting the color preference of a beauty light based on the light source correlated color temperature, Duv, illuminance, and light source whiteness. It relies on the correlated color temperature, Duv, and illuminance indicators of the light source to be predicted, and uses the combination of on-site vision and live scene preference prediction and estimation models as a means to achieve a comprehensive and accurate prediction and evaluation of the color preference of the light source to be predicted under the influence of the light source color temperature, Duv, illuminance, and light source whiteness, and selects the corresponding target spectral parameter value according to the target color preference obtained by the preference prediction to accurately adjust the lamp. This expands the adjustment range of the lamp and improves the flexibility and adjustment effect of the lamp.

[0199] In this embodiment, a lamp adjustment device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the terms "module" and "device" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0200] According to an embodiment of the present invention, there is also provided an embodiment of a device for implementing the above-mentioned lamp adjustment method. Figure 5 is a schematic diagram of the structure of a lamp adjustment device according to an embodiment of the present invention. Figure 5 As shown, the above-mentioned lamp adjustment device includes: a lighting mode determination module 500, a color preference determination module 502, a first parameter determination module 504, and a first adjustment module 506, wherein:

[0201] A lighting mode determination module 500, used to determine the lighting mode of the lamp;

[0202] A color preference determination module 502, connected to the lighting mode determination module 500, is used to determine the on-site visual color preference and the live scene color preference according to the lighting mode, wherein the on-site visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in the real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in the live scene;

[0203] A first parameter determination module 504, connected to the color preference determination module 502, for determining a target parameter value of a target spectrum parameter of the lamp based on the on-site visual color preference and the live scene color preference;

[0204] The first adjustment module 506 is connected to the first parameter determination module 504 and is used to adjust the lamp based on the target parameter value.

[0205] By setting the lighting mode determination module 500, the color preference determination module 502, the first parameter determination module 504, and the first adjustment module 506, the purpose of combining the lighting mode, selecting spectral parameters and adjusting the lamps can be achieved from the two aspects of on-site vision and live broadcast scene, thereby achieving the technical effect of expanding the adjustment range of the lamps and improving the adjustment effect of the lamps, and further solving the technical problem in the related technology that the factors are not fully considered when adjusting the lamps, resulting in a small adjustment range of the lamps and poor adjustment effect of the lamps.

[0206] According to an embodiment of the present invention, another device embodiment for implementing the above-mentioned lamp adjustment method is also provided. Figure 6 is a schematic diagram of the structure of a lamp adjustment device according to an embodiment of the present invention. Figure 6 As shown, the above-mentioned lamp adjustment device includes: a parameter acquisition module 600, a color preference acquisition module 602, a second parameter determination module 604, and a second adjustment module 606, wherein:

[0207] The parameter acquisition module 600 is used to acquire multiple groups of spectral parameter values ​​of the lamp, wherein each group of spectral parameter values ​​includes parameter values ​​of multiple spectral parameters;

[0208] A color preference acquisition module 602, connected to the parameter acquisition module 600, is used to acquire the on-site visual color preference and the live scene color preference corresponding to the multiple sets of spectral parameter values, wherein the on-site visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in the real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in the live scene;

[0209] The second parameter determination module 604 is connected to the color preference acquisition module 602, and is used to determine the target group parameter value from the multiple groups of spectral parameter values ​​based on the on-site visual color preference, the live scene color preference, and the lighting mode of the lamp corresponding to the multiple groups of spectral parameter values, wherein the target group parameter value includes the target parameter values ​​of the multiple spectral parameters respectively;

[0210] The second adjustment module 606 is connected to the second parameter determination module 604 and is used to adjust the lamp according to the target group parameter value.

[0211] By setting the parameter acquisition module 600, the color preference acquisition module 602, the second parameter determination module 604, and the second adjustment module 606, the purpose of combining the lighting mode, selecting spectral parameters and adjusting the lamps from the two aspects of on-site vision and live broadcast scene can be achieved, thereby achieving the technical effect of expanding the adjustment range of the lamps and improving the adjustment effect of the lamps, and further solving the technical problem in the related technology that the factors are not fully considered when adjusting the lamps, resulting in a small adjustment range of the lamps and poor adjustment effect of the lamps.

[0212] It should be noted that the above modules can be implemented by software or hardware. For example, for the latter, it can be implemented in the following ways: the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0213] It should be noted that the lighting mode determination module 500, the color preference determination module 502, the first parameter determination module 504, and the first adjustment module 506 correspond to steps S102 to S108 in the embodiment, and the parameter acquisition module 600, the color preference acquisition module 602, the second parameter determination module 604, and the second adjustment module 606 correspond to steps S302 to S308 in the embodiment. The examples and application scenarios implemented by the above modules and the corresponding steps are the same, but are not limited to the contents disclosed in the above embodiments. It should be noted that the above modules as part of the device can be run in a computer terminal.

[0214] It should be noted that the optional or preferred implementation of this embodiment can refer to the relevant description in the embodiment, which will not be repeated here.

[0215] The above-mentioned lamp adjustment device may further include a processor and a memory. The above-mentioned modules are stored in the memory as program modules, and the processor executes the above-mentioned program modules stored in the memory to realize corresponding functions.

[0216] The processor includes a kernel, which retrieves the corresponding program module from the memory. The kernel may be one or more. The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. The memory includes at least one memory chip.

[0217] According to an embodiment of the present application, a lamp is also provided, which includes the lamp adjustment device mentioned above.

[0218] According to an embodiment of the present application, an embodiment of a non-volatile storage medium is also provided. Optionally, in this embodiment, the non-volatile storage medium includes a stored program, wherein when the program is executed, the device where the non-volatile storage medium is located is controlled to execute any of the above-mentioned lamp adjustment methods.

[0219] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group, and the non-volatile storage medium includes a stored program.

[0220] Optionally, when the program is running, the device where the non-volatile storage medium is located is controlled to perform the following functions: determine the lighting mode of the lamp; determine the on-site visual color preference and the live scene color preference according to the lighting mode, wherein the on-site visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in the real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in the live scene; based on the on-site visual color preference and the live scene color preference, determine the target parameter value of the target spectral parameter of the lamp; and adjust the lamp based on the target parameter value.

[0221] According to an embodiment of the present application, an embodiment of a processor is also provided. Optionally, in this embodiment, the processor is used to run a program, wherein the program executes any one of the above-mentioned lamp adjustment methods when it is run.

[0222] According to an embodiment of the present application, an embodiment of a computer program product is also provided. When executed on a data processing device, the computer program product is suitable for executing a program that initializes any of the above-mentioned lamp adjustment method steps.

[0223] Optionally, the above-mentioned computer program product, when executed on a data processing device, is suitable for executing a program that initializes the following method steps: determining a lighting mode of the lamp; determining a live visual color preference and a live scene color preference based on the lighting mode, wherein the live visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a live scene; based on the live visual color preference and the live scene color preference, determining a target parameter value of a target spectral parameter of the lamp; and adjusting the lamp based on the target parameter value.

[0224] An embodiment of the present invention provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the program: determining a lighting mode of a lamp; determining a live visual color preference and a live scene color preference according to the lighting mode, wherein the live visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a live scene; determining a target parameter value of a target spectral parameter of the lamp based on the live visual color preference and the live scene color preference; and adjusting the lamp based on the target parameter value.

[0225] The above sequence of the embodiments of the present invention is for description only and does not represent the superiority or inferiority of the embodiments.

[0226] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0227] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the above modules can be a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, modules or indirect coupling or communication connection of modules, which can be electrical or other forms.

[0228] The modules described above as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0229] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of software functional modules.

[0230] If the above-mentioned integrated module is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable non-volatile storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a non-volatile storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the various embodiments of the present invention. The aforementioned non-volatile storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0231] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A lamp adjustment method, characterized in that: include: Determine the lighting mode of the lamp; Determine, according to the lighting mode, a live visual color preference and a live scene color preference, wherein the live visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a live scene; Determining a target parameter value of a target spectral parameter of the lamp based on the on-site visual color preference and the live scene color preference; The lamp is adjusted based on the target parameter value.

2. The method according to claim 1, characterized in that Determining the on-site visual color preference and the live scene color preference according to the lighting mode includes: Obtaining a preset target color preference, wherein the target color preference is used to indicate a comprehensive color preference for the lighting source generated by the lamp; Determine, according to the lighting mode, a first weight coefficient corresponding to the on-site visual color preference and a second weight coefficient corresponding to the live scene color preference; Determining a target ratio coefficient between the on-site visual color preference and the live scene color preference; The on-site visual color preference and the live scene color preference are determined based on the target color preference, the first weight coefficient, the second weight coefficient, and the target scale coefficient.

3. The method according to claim 2, characterized in that The determining of the target ratio coefficient between the on-site visual color preference and the live scene color preference includes: Acquiring a scene preference, wherein the scene preference is used to indicate a preference for a live visual scene and a live broadcast scene; According to the scene preference, the target ratio coefficient between the on-site visual color preference and the live scene color preference is determined.

4. The method according to claim 1, characterized in that: The step of determining the target parameter value of the target spectral parameter of the lamp based on the on-site visual color preference and the live scene color preference includes: Based on the on-site visual color preference and the live scene color preference, a spectral parameter prediction model is used to obtain the target parameter value of the target spectral parameter, wherein the spectral parameter prediction model pre-learns the correlation between the target spectral parameter and the on-site visual color preference and the live scene color preference.

5. The method according to claim 4, characterized in that In the case where the spectral parameter prediction model includes a first spectral parameter prediction model and a second spectral parameter prediction model, the spectral parameter prediction model is used based on the on-site visual color preference and the live scene color preference to obtain the target parameter value of the target spectral parameter, including: Get the scene preference type; In the case where the scene preference type is the first preference type, based on the on-site visual color preference and the live scene color preference, the first spectral parameter prediction model is used to obtain the target parameter value, wherein the first preference type is used to indicate that the preference for the on-site visual scene is greater than the preference for the live scene; or In the case where the scene preference type is the second preference type, the target parameter value is obtained by using the second spectral parameter prediction model based on the on-site visual color preference and the live scene color preference, wherein the second preference type is used to indicate that the preference for the on-site visual scene is less than the preference for the live scene.

6. The method according to claim 4, characterized in that The step of adjusting the lamp based on the target parameter value includes: Detecting whether the target parameter value is within a predetermined parameter range; When the target parameter value is not within the predetermined parameter range, the target parameter value is optimized, and the lamp is adjusted based on the optimized target parameter value.

7. The method according to claim 1, characterized in that The step of adjusting the lamp based on the target parameter value includes: In the case where it is detected that the parameter values ​​of other spectral parameters of the lamp need to be optimized, based on the new on-site visual color preference and the new live scene color preference, the optimized parameter values ​​of the other spectral parameters are obtained, wherein the other spectral parameters are spectral parameters other than the target spectral parameters among the multiple spectral parameters of the lamp; The lamp is adjusted based on the target parameter value and the optimized parameter value.

8. The method according to any one of claims 1 to 7, characterized in that The lamp has multiple spectral parameters, and the multiple spectral parameters include the target spectral parameter and other spectral parameters, wherein the parameter values ​​of the other spectral parameters are preset values.

9. A lamp adjustment method, characterized in that: include: Acquire multiple groups of spectral parameter values ​​of the lamp, wherein each group of spectral parameter values ​​includes respective parameter values ​​of multiple spectral parameters; Obtaining the on-site visual color preference and the live scene color preference corresponding to the multiple groups of spectral parameter values, respectively, wherein the on-site visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a live scene; Based on the on-site visual color preferences, live scene color preferences, and the lighting mode of the lamp corresponding to the multiple groups of spectral parameter values, a target group parameter value is determined from the multiple groups of spectral parameter values, wherein the target group parameter value includes the target parameter values ​​of the multiple spectral parameters respectively; The lamp is adjusted according to the target group parameter value.

10. The method according to claim 9, characterized in that The step of determining a target group parameter value from the multiple groups of spectral parameter values ​​based on the on-site visual color preference, the live scene color preference, and the lighting mode of the lamp respectively corresponding to the multiple groups of spectral parameter values ​​includes: Based on the lighting mode, determining a first weight coefficient corresponding to the on-site visual color preference and a second weight coefficient corresponding to the live scene color preference; Based on the on-site visual color preferences and live scene color preferences corresponding to the multiple groups of spectral parameter values, the first weight coefficient, and the second weight coefficient, determine the target color preferences corresponding to the multiple groups of spectral parameter values, wherein the target color preference is used to indicate the comprehensive color preference for the lighting source generated by the lamp; The target group parameter value is determined from the multiple groups of spectral parameter values ​​based on the target color preference degrees respectively corresponding to the multiple groups of spectral parameter values.

11. The method according to claim 9, characterized in that In the case where the multiple spectral parameters include at least color temperature, chromaticity deviation value, and illumination, obtaining the on-site visual color preference and the live scene color preference corresponding to the multiple groups of spectral parameter values ​​respectively includes: Based on the color temperature in any set of parameter values, determine the on-site visual related color temperature influence factor and the live scene related color temperature influence factor, wherein the on-site visual related color temperature influence factor is used to evaluate the influence of the light source color temperature on the on-site visual effect, and the live scene related color temperature influence factor is used to evaluate the influence of the light source color temperature on the live picture effect; Based on the illumination in any group of parameter values, determining a scene visual illumination influence factor, wherein the scene visual illumination influence factor is used to evaluate the influence of illumination on scene visual effects; According to the on-site visual correlated color temperature influence factor, the on-site visual illuminance influence factor and the chromaticity deviation value in any one group of parameter values, obtaining the on-site visual color preference corresponding to any one group of parameter values; According to the live scene related color temperature influencing factor and the chromaticity deviation value in any group of parameter values, obtaining the live scene color preference corresponding to any group of parameter values; By adopting the method of obtaining the on-site visual color preference and the live scene color preference corresponding to any one group of parameter values, the on-site visual color preference and the live scene color preference corresponding to multiple groups of spectral parameter values ​​are obtained.

12. A lamp adjustment device, characterized in that: include: A lighting mode determination module, used to determine the lighting mode of the lamp; A color preference determination module, used to determine the on-site visual color preference and the live scene color preference according to the lighting mode, wherein the on-site visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a live scene; A first parameter determination module, used to determine a target parameter value of a target spectral parameter of the lamp based on the on-site visual color preference and the live scene color preference; The first adjustment module is used to adjust the lamp based on the target parameter value.

13. A lamp adjustment device, characterized in that: include: A parameter acquisition module, used to acquire multiple groups of spectral parameter values ​​of the lamp, wherein each group of spectral parameter values ​​includes parameter values ​​of multiple spectral parameters; A color preference acquisition module, used to acquire the on-site visual color preference and the live scene color preference corresponding to the multiple groups of spectral parameter values, wherein the on-site visual color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a real environment, and the live scene color preference is used to indicate the degree of preference for the color of the lighting source generated by the lamp in a live scene; A second parameter determination module is used to determine a target group parameter value from the multiple groups of spectral parameter values ​​based on the on-site visual color preference, the live scene color preference, and the lighting mode of the lamp corresponding to the multiple groups of spectral parameter values, wherein the target group parameter value includes the target parameter values ​​of the multiple spectral parameters respectively; The second adjustment module is used to adjust the lamp according to the target group parameter value.

14. A lamp, characterized in that: The lamp comprises the lamp adjustment device described in claim 12 or 13.

15. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the lamp adjustment method described in any one of claims 1 to 11.

16. An electronic device, characterized in that: It comprises one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the lamp adjustment method described in any one of claims 1 to 11.

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