Control method and device for cabin lighting equipment

Abstract

The present disclosure provides a control method and device for in-cabin lighting equipment. A control method for in-cabin lighting equipment includes: dividing the lighting equipment into a plurality of visual zones; obtaining a theme image, dividing the theme image into a plurality of image zones, so that each image zone has an associated spatial correspondence with each visual zone in the occupant's field of view; and determining the optical parameters of the lighting equipment of each visual zone based on the image information and spatial correspondence of each image zone. Based on the spatial correspondence between the visual zone and the image zone, the theme image is reproduced on the interior lighting, and the immersive visual experience of the occupant is improved.

Description

Technical Field

[0001] This disclosure relates to the field of vehicles, and more specifically, to a control method for cabin lighting equipment, a vehicle, a control system for cabin lighting equipment, a computing device, a computer-readable storage medium having computer-executable instructions stored thereon, and a computer program product. Background Technology

[0002] With the continuous development of the automotive industry, vehicles are no longer merely seen as a means of transportation, but have gradually evolved into personalized mobile spaces that integrate travel, rest, and entertainment. To create a more comfortable, pleasant, and stylish driving environment, interior lighting equipment is increasingly being used in modern cars. This lighting equipment typically includes LED light strips (commonly known as "ambient lighting") embedded in door panels, center consoles, footwells, or dashboards, as well as displays such as the center screen, capable of emitting light of various colors and brightness. Through precise control of this light, the visual depth and design aesthetics of the interior can be effectively enhanced, providing passengers with a more refined travel experience. Summary of the Invention

[0003] The purpose of this disclosure is to provide a control method for cabin lighting equipment, enabling more precise and personalized control of the lighting equipment.

[0004] According to a first aspect of this disclosure, a control method for an in-cabin lighting device is provided, comprising: dividing the lighting device into multiple visual zones; obtaining a subject image, dividing the subject image into multiple image zones such that each image zone and each visual zone have an associated spatial correspondence in the occupant's field of vision; and determining the optical parameters of the lighting device for each visual zone based on the image information of each image zone and the spatial correspondence.

[0005] In some embodiments, the plurality of visual partitions are distributed along a first direction, and dividing the subject image into a plurality of image partitions includes: dividing the subject image into a plurality of image partitions along the first direction, wherein the number of the plurality of image partitions corresponds to the number of the plurality of visual partitions.

[0006] In some embodiments, dividing the subject image into multiple image partitions includes: adjusting the size of each image partition along the first direction such that the size is proportional to the number of illumination units in the corresponding visual partition.

[0007] In some embodiments, dividing the subject image into multiple image partitions includes: using an image semantic recognition model to perform image semantic recognition on the subject image to obtain multiple semantic regions; and determining the multiple image partitions based on the multiple semantic regions.

[0008] In some embodiments, the plurality of visual partitions are distributed along a first direction, and determining the plurality of image partitions based on the plurality of semantic regions includes: merging and sorting the plurality of semantic regions according to a preset visual cognition hierarchy to obtain the plurality of image partitions corresponding to each level in the visual cognition hierarchy, wherein the number of the plurality of image partitions corresponds to the number of the plurality of visual partitions, and the order of each image partition along the first direction corresponds to the distribution order of each visual partition in the occupant's field of vision.

[0009] In some embodiments, determining the optical parameters of the lighting device for each visual partition based on the image information of each image partition and the spatial correspondence includes: extracting candidate colors from each image partition and calculating the color proportion of each candidate color in the image partition; selecting from the candidate colors at least twice to generate multiple color combinations, each color combination including at least two candidate colors; calculating the combination proportion of each color combination in the image partition according to the color proportion, and calculating the hue difference between the candidate colors in each color combination, thereby determining a target color combination from the multiple color combinations based on the combination proportion and the hue difference; and determining the color of the lighting device for the visual partition corresponding to the image partition based on the target color combination.

[0010] In some embodiments, extracting candidate colors from the image partition includes: extracting multiple colors from the image partition in the HSV color space of the subject image; and filtering out colors with brightness values ​​lower than a brightness threshold, and using the remaining colors as the candidate colors.

[0011] In some embodiments, determining the optical parameters of the lighting devices for each visual partition based on the image information of each image partition and the spatial correspondence further includes: obtaining target color combinations for two adjacent visual partitions; determining whether the color parameter difference between the two target color combinations exceeds a color parameter difference threshold; if the color parameter difference exceeds the color parameter difference threshold, generating a transition color sequence that gradually changes from one target color combination to another; and determining the color of at least a portion of the lighting devices in the two adjacent visual partitions based on the transition color sequence, so that the colors of the two adjacent visual partitions transition smoothly.

[0012] In some embodiments, an image generation model is used to generate the subject image based on occupant input, wherein the input includes at least one of voice, touch signals, and facial capture images.

[0013] In some embodiments, the method further includes: obtaining state data, the state data including at least one of occupant state data, vehicle state data, and environmental state data; determining the current scenario of the occupant based on the state data, wherein the current scenario includes one of a driving scenario, an entertainment scenario, a rest scenario, and a warning scenario; and determining optical parameters of lighting devices for at least one preset zone according to the current scenario, wherein the preset zone includes at least one of a dashboard area, a door panel area, and a headliner area.

[0014] In some embodiments, the method further includes dividing the lighting device into multiple visual zones based on the occupant seat position, occupant head position, occupant eye position, the center position of multiple occupant positions, or a designated position inside the vehicle.

[0015] In some embodiments, the method further includes: obtaining theme audio; and determining optical parameters of lighting devices for a preset zone based on sound effect information of the theme audio.

[0016] In some embodiments, the subject audio is generated by an audio generation model based on occupant input, wherein the input includes at least one of speech, touch signals, and facial capture images.

[0017] In some embodiments, the method further includes controlling the lighting device based on determined optical parameters, wherein controlling the lighting device includes: controlling a first group of visual partitions in the lighting device via a first communication link; controlling a second group of visual partitions in the lighting device via a second communication link, wherein the first group has a higher visual priority than the second group, and wherein the first communication link provides an independent link for each visual partition in the first group, and the second communication link provides a shared link for all visual partitions in the second group.

[0018] In some embodiments, the first set of visual partitions includes an instrument panel area; the second set of visual partitions includes a door panel area and a headliner area; and the first communication link and the second communication link are communication links based on the vehicle's controller area network.

[0019] According to a second aspect of this disclosure, a vehicle is provided, including: interior lighting equipment; and a controller configured to perform the method described according to any embodiment of the first aspect of this disclosure.

[0020] According to a third aspect of this disclosure, a control system for cabin lighting equipment is provided, comprising: an external input device including at least one of a voice acquisition unit, a touch acquisition unit, and an image acquisition unit; a domain controller including a communication unit and a multimodal data processing unit configured to perform the method described according to any embodiment of the first aspect of this disclosure; and an execution module including a light controller and lighting equipment, wherein the communication unit is configured to communicate with a cloud processing module including a generative unit, the external input device, and the execution module, respectively.

[0021] According to a fourth aspect of this disclosure, a computing device is provided, comprising: one or more processors; and a memory storing computer-executable instructions, which, when executed by the one or more processors, cause the one or more processors to perform the method according to any embodiment of the first aspect of this disclosure.

[0022] According to a fifth aspect of this disclosure, a computer-readable storage medium is provided having computer-executable instructions stored thereon, which, when executed by a computer, cause the computer to perform the method described according to any embodiment of the first aspect of this disclosure.

[0023] According to a sixth aspect of this disclosure, a computer program product is provided, the computer program product including instructions that, when executed by a processor, implement the method according to any embodiment of the first aspect of this disclosure.

[0024] Other features and advantages of this disclosure will become clearer from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0025] The foregoing and other features and advantages of this disclosure will become clear from the following description of embodiments illustrated in conjunction with the accompanying drawings. The drawings, incorporated herein and forming a part of the specification, are further used to explain the principles of this disclosure and to enable those skilled in the art to make and use it. Wherein: Figure 1 This is a schematic flowchart illustrating a control method for cabin lighting equipment according to some embodiments of the present disclosure; Figure 2 This is an example illustration of the distribution diagram for cabin lighting equipment; Figure 3 This is a schematic diagram illustrating a non-limiting example process of dividing a subject image into multiple image partitions; Figure 4This is a flowchart illustrating a non-limiting example process in which a control method for cabin lighting equipment according to some embodiments of the present disclosure is applied; Figure 5 This is a schematic block diagram illustrating a vehicle according to some embodiments of the present disclosure; Figure 6 This is a schematic block diagram illustrating a control system for cabin lighting equipment according to some embodiments of the present disclosure; Figure 7 This is a schematic block diagram illustrating a computing device according to some embodiments of the present disclosure; Figure 8 This is a schematic block diagram illustrating a computer system on which embodiments of the present disclosure may be implemented.

[0026] Note that in the embodiments described below, the same reference numerals are sometimes used across different figures to denote the same parts or parts having the same function, and repeated descriptions are omitted. In this specification, similar reference numerals and letters are used to denote similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0027] For ease of understanding, the positions, dimensions, and extents of the structures shown in the accompanying drawings and other materials may not represent actual positions, dimensions, and extents. Therefore, the disclosed invention is not limited to the positions, dimensions, and extents disclosed in the accompanying drawings and other materials. Furthermore, the drawings are not necessarily drawn to scale, and some features may be enlarged to show details of specific components. Detailed Implementation

[0028] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present disclosure.

[0029] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit this disclosure or its application or use. Those skilled in the art will understand that they merely illustrate exemplary ways that can be used to implement this disclosure, and are not exhaustive.

[0030] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0031] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0032] Currently, the control methods for cabin lighting equipment are relatively basic. Common practices involve occupants manually adjusting the overall brightness or on / off status of all interior lighting equipment by pressing physical buttons or operating the central control screen; alternatively, the system may have a few built-in fixed lighting modes for occupants to choose from, such as "bright mode" or "soft mode." Such adjustment methods are rather crude and cannot achieve more refined lighting effects.

[0033] Based on the above, this disclosure provides a control method for cabin lighting equipment. This method divides the lighting equipment into zones according to the occupant's eye position and correspondingly divides the theme image into zones, creating a spatial correspondence between the two in the occupant's field of vision. Then, the optical parameters of the corresponding lighting equipment are determined based on the content of each image zone. This approach allows the lighting effects in different areas of the vehicle interior to match the occupant's visual perception and the content of the theme image, thereby creating a more spatially layered and visually harmonious light and shadow atmosphere inside the cabin, achieving more refined and personalized control of the lighting equipment.

[0034] The control method for the cabin lighting equipment will now be described in detail with reference to the accompanying drawings. It will be understood that the actual method may include other steps, but these are not shown in the drawings and will not be discussed herein in order to avoid obscuring the key points of this disclosure.

[0035] Figure 1 A flowchart of a control method 100 for cabin lighting equipment according to some embodiments of the present disclosure is shown. Figure 1 As shown, method 100 includes steps S102 to S106.

[0036] In this disclosure, "cabin interior" refers to a limited space that allows personnel to enter, including but not limited to passenger cabins in vehicles, aircraft cabins, ship cabins, and other modes of transportation, as well as / or other non-transportation habitable cabins such as sleep pods, physiotherapy pods, and live broadcast pods. For ease of description and understanding, the technical solutions of this disclosure are mainly illustrated using vehicle cabins as an example below. However, those skilled in the art will understand that this disclosure is not limited to this and can also be applied to other types of cabin interior environments.

[0037] In step S102, the lighting equipment is divided into multiple visual zones.

[0038] The lighting devices in this disclosure can be distributed in multiple locations within the vehicle interior, see reference. Figure 2Part A is a side view of the example vehicle interior, and Part B is a front view of the example vehicle interior from the inside out. For example, in the door panel (DP) area where lighting devices L1 and L3 are located, the instrument panel (IP) area where lighting device L2 is located, the roof area where lighting device L4 is located, and other areas such as the footwell where lighting device L5 is located, each lighting device has a fixed three-dimensional coordinate in the vehicle interior space.

[0039] Based on this, the lighting equipment can be divided into multiple visual zones. A visual zone refers to a lighting area divided according to the occupant's spatial perception inside the vehicle, with each visual zone corresponding to a specific location in the occupant's field of vision.

[0040] In this article, "occupant" refers to the person inside the cabin. Taking the vehicle cabin as an example, "occupant" can be a person located inside the vehicle, including but not limited to the driver and passengers.

[0041] In some embodiments, visual partitions may include three partitions: top, middle, and bottom. It is understood that the number of visual partitions is not limited to three; it can be fewer or more. Furthermore, the partitioning direction may include other directions such as left-right, front-back, or multiple directions simultaneously.

[0042] To achieve this division, in some embodiments, the lighting equipment can be divided into multiple visual zones based on the position of the occupant's seat, the position of the occupant's head, the position of the occupant's eyes, the center position of multiple occupant positions, or a designated position inside the vehicle.

[0043] When dividing the lighting equipment into vertical zones, a specific position of the occupant within the cabin can be used as a reference for division. In some embodiments, when using the seat position as a reference, different seats can have different preset height values, and the corresponding visual zone boundary can be determined based on the height of the occupant's seat. When using the head position as a reference, the zone boundary is determined by obtaining the spatial coordinates of the occupant's head. More precisely, when using the eye position as a reference, for example, as shown... Figure 2 As shown in Part B, the first direction can be the vertical direction as illustrated. For taller occupants, the upper visual zone S1 can include lighting device L4, the middle visual zone S2 can include lighting devices L1, L2, and L3, and the lower visual zone S3 can include lighting device L5. For shorter occupants, due to the reduced eye height, lighting device L2 can be classified into the upper visual zone.

[0044] Alternatively or additionally, when using the center position of multiple occupant positions as a reference, the average value of each occupant position (e.g., occupant seat position) can be calculated first as the center position, and then the partition boundaries can be determined using this center position. When using a designated position within the cabin as a reference, the user-inputted or system-preset coordinate points can be directly used as the partitioning basis. In cases where no one is riding or occupant positions are not considered, the vehicle center position, driver's position, or executive seat position can also be directly used as a preset reference to simplify configuration and facilitate unified layout by the vehicle manufacturer.

[0045] When dividing lighting equipment into zones based on left-right or front-back directions, the passenger seat position can be used as a reference for division. That is, whether the passenger is in the driver's seat, front passenger seat, or rear seat, this determines the front-back and left-right distribution of the lighting equipment in their field of vision. Since the division principle is similar to that of the up-down direction, it will not be elaborated here.

[0046] The aforementioned occupant position information can be obtained in various ways. For example, seat position can be determined by combining seat pressure sensors with seat position information. Head and eye positions can be determined by capturing facial images of the occupants using an in-vehicle camera and extracting their spatial coordinates using image recognition algorithms. By combining the above information, the three-dimensional coordinates of the selected reference point in the vehicle's interior space can be determined, and then the lighting equipment can be divided into sections by combining these coordinates with the fixed three-dimensional coordinates of each lighting device.

[0047] In step S104, a subject image is obtained and divided into multiple image partitions, such that each image partition and each visual partition have an associated spatial correspondence in the occupant's field of vision.

[0048] In some embodiments, an image generation model may be used to generate a subject image based on occupant input, wherein the input includes at least one of voice, touch signals, and facial capture images.

[0049] Regarding voice commands, for example, passengers can describe "sunset over the western mountains" using voice. After receiving the voice command, the system converts it into a text description, and then an image generation model generates a corresponding image based on this description. Figure 3 As shown in Part A. Touch signals can come from the central control screen or the occupant's mobile device. The occupant can select image styles, draw simple patterns, or input keywords through touch operations, and these touch interaction information can be used as the basis for image generation. Facial capture images are obtained by collecting the occupant's facial information through an in-vehicle camera, recognizing facial features, emotional states, etc., and then using them as reference factors when the image generation model generates the subject image.

[0050] Image generation models can be generative models based on artificial intelligence (AI), and their implementation methods include, but are not limited to, diffusion models. These models can generate visual images that match the input description or reflect the input characteristics based on input text, images, or emotional information.

[0051] In addition to these methods, the subject image can also be obtained in various other ways. For example, occupants can directly upload images stored on their mobile devices or in-vehicle storage as the subject image; or they can obtain the subject image in real time through external or internal vehicle cameras. Furthermore, the subject image can also be a frame extracted from a video, which can also be an AI-generated video, a video uploaded by an occupant, or a video captured by a camera.

[0052] In this way, the system can flexibly obtain thematic images that match the occupant's expectations, emotions, or environment based on the occupant's individual needs or current state.

[0053] The following describes how to segment the subject image.

[0054] In some embodiments, the plurality of visual partitions are distributed along a first direction, and dividing the subject image into a plurality of image partitions includes: dividing the subject image into a plurality of image partitions along the first direction, wherein the number of the plurality of image partitions corresponds to the number of the plurality of visual partitions.

[0055] The first direction refers to the spatial direction used when dividing visual zones, such as the up-down direction, the left-right direction, or the front-back direction. For ease of explanation, the following description will use the up-down direction as an example. Those skilled in the art will understand that embodiments in other directions can be extended by referring to the embodiments in the up-down direction.

[0056] The direction of the subject image division is consistent with the direction of the visual partition division. Regarding the number of partitions, the number of image partitions can be the same as the number of visual partitions, allowing each image partition to establish a one-to-one correspondence with a visual partition. For example, if the visual partitions are divided into upper, middle, and lower sections along the vertical direction, then the subject image is also correspondingly divided into upper, middle, and lower image partitions along the vertical direction. It can be understood that besides a one-to-one correspondence, other correspondences can also exist between visual and image partitions. For example, their numbers can be in a certain proportion; alternatively, if the number of image partitions is greater than the number of visual partitions, multiple image partitions can be merged and mapped to the same visual partition, or some image partitions can be selected for correspondence. Conversely, the number of image partitions can be less than the number of visual partitions, in which case one image partition can correspond to multiple visual partitions. Regardless of the quantitative relationship used, it is sufficient to ensure that the image partitions and visual partitions can form a logical correspondence in spatial orientation.

[0057] This division method establishes a spatial correspondence between each image zone and each visual zone within the occupant's field of vision. When an occupant observes the interior environment, the upper part of their field of vision corresponds to the upper area of ​​the main image, and the lower part corresponds to the lower area of ​​the main image. Therefore, the lighting effects perceived from different angles within the occupant's field of vision correspond to the image content in the corresponding areas of the main image, creating a visual experience within the cabin that aligns with the composition and layout of the main image.

[0058] Furthermore, in some embodiments, dividing the subject image into multiple image partitions may include: adjusting the size of each image partition along a first direction such that the size is proportional to the number of illumination units in the corresponding visual partition.

[0059] The number of lighting units can refer to the number of basic units of lighting equipment within a visual partition. For example, when the lighting equipment includes light strips, the number of lighting units can be the number of LEDs in the light strip. In other words, the more lighting equipment arranged within a visual partition, or the larger the size of the lighting equipment, the larger the corresponding image partition size. For example, suppose a visual partition is divided into three sections along the vertical direction: upper, middle, and lower. The upper visual partition contains one lighting device, the middle visual partition contains six lighting devices, and the lower visual partition contains two lighting devices. If the size of the image partition is adjusted according to the proportional relationship of the number of lighting units within each visual partition, the subject image can be divided into three image partitions with a size ratio of 1:6:2 along the vertical direction. In this way, the middle visual partition, with the most lighting units, has the largest corresponding image partition, thus enabling the extraction of richer color, brightness, and other information from the subject image to support fine-grained control of multiple lighting devices.

[0060] It is understandable that when multiple directions are divided simultaneously (such as dividing along the vertical and horizontal directions at the same time), the size of the image partition can be adjusted according to the distribution of illumination units in each direction, thereby forming a grid-like non-uniform partition.

[0061] For illustrative purposes, a non-restrictive implementation process is as follows: Figure 3 As shown, Figure 3 Sections A through F sequentially display the intermediate results of each processing step. We can first... Figure 3 The subject image shown in Part A is divided into uniform grid cells (e.g., Figure 3 As shown in Part B), each grid cell is analyzed to determine whether it contains valid image information. For example, the proportion of dark pixels within the grid can be calculated; if the proportion of dark pixels exceeds a preset threshold, the grid is marked as invalid (e.g., ...). Figure 3 (As shown in the red grid in section C) and filtered to prevent image areas with no substantial content from affecting subsequent lighting control effects.

[0062] Subsequently, as Figure 3 As shown in section D, the remaining grid after filtering is grouped according to the row direction of the image. As mentioned earlier, the number of grid rows can be allocated according to the weight of each visual partition in the vertical direction, that is, the more densely lit visual partitions are allocated more grid rows, and each visual partition is allocated at least one grid row. In a non-limiting embodiment, when the lighting device contains 4 visual partitions, they correspond to... Figure 3 The areas corresponding to the yellow, green, purple, and pink grids in section D. These four visual zones are distributed along the first direction shown in the figure.

[0063] Next, as Figure 3 As shown in section E, within the grid row group corresponding to each visual partition, the largest matrix region that is continuously arranged in the horizontal direction is identified. This step can eliminate fragmented grids caused by filtering, ensuring spatial continuity of the image area corresponding to each visual partition and avoiding jumps or breaks in lighting effects due to discontinuity.

[0064] Finally, as Figure 3As shown in section F, within the continuous matrix region corresponding to each visual partition, the grid rows are further divided into several sub-regions according to the horizontal distribution of the lighting devices within that visual partition. For example, if a visual partition contains multiple lighting devices distributed horizontally, the grid rows corresponding to that partition are divided into a corresponding number of sub-regions based on the number of lighting devices, so that each sub-region corresponds to one or a group of lighting devices. This non-uniform division method, combining vertical and horizontal directions, allows for a more precise match between the final image partitions and the actual spatial distribution of the vehicle's lighting devices, thus providing more targeted image information guidance for each lighting device and achieving a more harmonious and layered lighting effect.

[0065] In other embodiments, dividing the subject image into multiple image partitions may include: using an image semantic recognition model to perform image semantic recognition on the subject image to obtain multiple semantic regions; and determining multiple image partitions based on the multiple semantic regions.

[0066] Image semantic recognition models are deep learning models built on artificial intelligence (AI) technology. They can classify pixels in an image and identify the object category to which each pixel belongs. Common implementations of image semantic recognition models include fully convolutional networks (FCNs), U-Net, and DeepLab.

[0067] After processing by an image semantic recognition model, the subject image is divided into multiple semantic regions, each corresponding to a set of consecutive pixels with the same semantic category in the subject image. For example, after semantic recognition, a landscape image may be divided into multiple semantic regions such as sky, mountains, water, and vegetation.

[0068] In some embodiments, determining multiple image partitions based on multiple semantic regions includes: merging and sorting multiple semantic regions according to a preset visual cognitive hierarchy to obtain multiple image partitions corresponding to each level in the visual cognitive hierarchy, wherein the number of multiple image partitions corresponds to the number of multiple visual partitions, and the order of each image partition along a first direction corresponds to the distribution order of each visual partition in the occupant's field of vision. The multiple visual partitions are distributed along the first direction.

[0069] Pre-defined visual cognitive levels refer to spatial hierarchies pre-defined based on human visual perception habits. For example, when observing an image, people typically categorize objects naturally as "upper area," "middle area," "lower area," or "left area," "middle area," "right area," or "foreground," "midground," "background," etc., based on their spatial location and semantic attributes. This cognitive hierarchy naturally corresponds to the distribution of visual zones within a vehicle along a certain direction (e.g., vertical, horizontal, or front-back). Merging and sorting multiple semantic regions involves grouping regions with similar levels according to their spatial location and semantic attributes within the image, and then arranging them according to their distribution order in the corresponding direction.

[0070] For example, suppose the visual space inside a car is divided into three sections along the vertical direction: upper, middle, and lower. By performing semantic recognition on a night sky landscape image, multiple semantic regions can be obtained, such as tree areas, river areas, grass areas, moon areas, and star areas. Based on a preset visual perception hierarchy, the moon and star areas can be merged into the upper region, corresponding to the upper visual section; the tree area can be used as the middle region, corresponding to the middle visual section; and the river and grass areas can be merged into the lower region, corresponding to the lower visual section.

[0071] Through the above merging and sorting, the final number of image partitions can correspond to the number of visual partitions (as mentioned before, the two can be equal or have other corresponding relationships, which will not be elaborated here), and the division direction of the image partitions is consistent with the division direction of the visual partitions.

[0072] Understandably, each of the aforementioned image partitioning methods has its own technical characteristics and applicable scenarios. Partitioning based on the proportion of lighting units allows for precise matching of image partitions with the actual spatial distribution of in-vehicle lighting equipment. Partitioning based on image semantic recognition, on the other hand, utilizes the ability of artificial intelligence models to understand image content, aggregating fragmented pixel information into regions with complete semantic meaning. This avoids chaotic lighting effects caused by overly complex image textures, and is more advantageous in creating an overall atmosphere. In practical applications, these methods can also be combined according to specific needs to balance the precision of control with the expressiveness of the atmosphere.

[0073] Back Figure 1 In step S106, the optical parameters of the lighting device for each visual zone are determined based on the image information and spatial correspondence of each image zone.

[0074] As mentioned earlier, each image partition and each visual partition have a spatial correspondence within the occupant's field of vision. The image information of each image partition refers to the visual features extracted from that partition, such as the dominant hue, average brightness, color distribution, and texture features within that partition. Based on the aforementioned spatial correspondence, the image information of each image partition can be used to determine the optical parameters of the lighting equipment within its corresponding visual partition.

[0075] Optical parameters can include color, brightness, and frequency of change. Among these, color information in image partitions can be used to determine the color of lighting equipment within the corresponding visual partition.

[0076] In some embodiments, determining the optical parameters of the lighting device for each visual partition based on the image information and spatial correspondence of each image partition includes: extracting candidate colors from each image partition and calculating the color proportion of each candidate color in the image partition; selecting from the candidate colors at least twice to generate multiple color combinations, each color combination including at least two candidate colors; calculating the combination proportion of each color combination in the image partition based on the color proportion, and calculating the hue difference between the candidate colors in each color combination, thereby determining a target color combination from the multiple color combinations based on the combination proportion and the hue difference; and determining the color of the lighting device for the visual partition corresponding to the image partition based on the target color combination.

[0077] Extracting candidate colors from each image partition means extracting colors for each image partition separately. Each image partition independently obtains a set of candidate colors and their proportions, and the color extraction between different image partitions does not interfere with each other.

[0078] For a given image partition, clustering algorithms (such as K-means, mean shift, etc.) can be used to group all pixels within the partition into several color categories based on color similarity. The color center corresponding to each category is a candidate color. After clustering, the proportion of pixels containing each candidate color to the total number of pixels in the image partition is calculated; this proportion is the color percentage of that candidate color. Besides clustering algorithms, other methods can also be used to extract colors. For example, the frequency of each pixel color in the image partition can be counted, and the most frequent colors can be selected as candidate colors. Another example is to divide the image partition into blocks, extract the representative color of each sub-block, and then merge or filter these representative colors to obtain candidate colors.

[0079] To further improve the effectiveness of candidate colors, in some embodiments, multiple colors in the image partitions are extracted in the HSV color space of the subject image; and colors with brightness values ​​below a brightness threshold are filtered out, with the remaining colors used as candidate colors.

[0080] The HSV color space consists of three dimensions: hue, saturation, and value. Compared to the RGB color space, HSV makes it easier to separate the hue and value of a color. By setting a value threshold (e.g., below 20%), overly dark or near-black colors in an image can be filtered out, as these colors often fail to produce effective color effects in lighting control. Ultimately, colors with high brightness and visual expressiveness can be selected as candidate colors.

[0081] Next, in some embodiments, a candidate color can be selected twice to generate multiple color combinations. When there are two or more candidate colors, different candidate colors can be selected for combination each time; when there is only one candidate color, that color is selected twice to form a color combination consisting of two identical candidate colors. It is understood that each color combination can also include more candidate colors (e.g., three), and correspondingly, more selections can be made from the candidate colors (e.g., three times), which will not be elaborated here.

[0082] Secondly, for each color combination, two metrics are calculated. The first is the combination percentage, which is the sum of the percentages of each candidate color within the combination obtained in the preceding steps, reflecting the overall weight of the color combination in the image partition. The second is the hue difference, which is the degree of difference between the candidate colors within the combination on the color wheel. When the candidate colors within the combination are the same, the hue difference is zero; when the candidate colors are complementary colors, the hue difference is 180°. When a combination contains more than two colors, the hue difference between all pairs of colors can be calculated, and the average or maximum value can be taken as the hue difference metric for that combination.

[0083] Then, based on the combination ratio and hue difference, a target color combination is determined from multiple color combinations. In some embodiments, a weighted scoring method can be used to rank the color combinations. For example, the combination ratio and hue difference can be weighted and summed according to preset weights (e.g., 50% each) to obtain a comprehensive score for each color combination, and then the color combination with the highest comprehensive score is selected as the target color combination. In this way, both the visual weight of color in the image partition and the contrast and harmony between colors are taken into account, so that the selected color combination can better reflect the overall color characteristics of the image partition.

[0084] Finally, based on the determined target color combination, the colors of the lighting devices within the corresponding visual zone of the image partition are set. If the target color combination contains only one color, all lighting devices within the visual zone are set to that color. If the target color combination contains two or more colors, the different colors in the combination can be assigned to different lighting devices within the visual zone based on the number and layout of the lighting devices and a preset allocation strategy. For example, the colors in the color combination can be assigned sequentially to lighting devices from left to right or from top to bottom according to the spatial distribution order of the lighting devices; the colors in the color combination can also be used as gradient colors to create a smooth color transition between the lighting devices within the zone; or the lighting devices can dynamically switch colors according to a certain time sequence to create flowing or alternating lighting effects. This can further enrich the visual experience inside the vehicle.

[0085] Understandably, when there is only one candidate color, the above process still applies, but you can directly use that color as the target color without having to perform the above combination selection process.

[0086] To further enhance the overall harmony of the lighting effects and avoid visual discontinuity caused by excessive color differences between adjacent visual zones, a smooth transition of colors between adjacent visual zones can be performed. In some embodiments, determining the optical parameters of the lighting devices for each visual zone based on the image information and spatial correspondence of each image zone further includes: acquiring target color combinations of two adjacent visual zones; determining whether the color parameter difference between the two target color combinations exceeds a color parameter difference threshold; if the color parameter difference exceeds the color parameter difference threshold, generating a transition color sequence that gradually changes from one target color combination to another; and determining the colors of at least some of the lighting devices in the two adjacent visual zones based on the transition color sequence, so as to achieve a smooth color transition between the two adjacent visual zones.

[0087] The target color combination for each visual zone can be determined through the aforementioned steps. Since each target color combination may contain multiple colors, it is necessary to determine a representative color for comparison. In some embodiments, a representative color can be selected from each target color combination for comparison. For example, the color with the highest proportion in each combination can be selected as the representative color. Alternatively, when colors within a combination are sequentially assigned to lighting devices, the color corresponding to the lighting device located at the boundary between two visual zones can be selected as the representative color, for example, comparing the color corresponding to the bottom lighting device in the upper visual zone with the color corresponding to the top lighting device in the lower visual zone. The color parameter difference can include at least one of hue difference and saturation difference. For example, a hue difference threshold (e.g., 30°) and a saturation difference threshold (e.g., 20%) can be set. When the hue difference between two representative colors exceeds 30° or the saturation difference exceeds 20%, it is determined that transition processing is required.

[0088] When the color parameter difference exceeds a threshold, a transitional color sequence is generated, gradually changing from one target color combination to another. This transitional color sequence can be several intermediate colors interpolated between the representative colors of the two target color combinations. For example, if the representative colors of two adjacent visual zones are red (hue 0°) and yellow (hue 60°), a transitional color sequence with hues of 10°, 20°, 30°, 40°, and 50° can be generated between them, forming a continuous gradient from red to yellow. When generating the transitional color sequence, the brightness of each transitional color can also be uniformly adjusted to remain within a preset brightness range (e.g., 0.4 to 0.95) to ensure moderate lighting brightness and visual comfort in the transition area.

[0089] Finally, the colors of at least some of the lighting devices in two adjacent visual zones are determined based on the transition color sequence. At least some lighting devices may refer to lighting devices located near the boundary between the two visual zones. In some embodiments, all lighting devices within the two visual zones can be sequentially assigned colors from the transition color sequence according to their spatial location, thereby creating a natural gradient effect across the entire zone. Through this method, even if the color differences between the image zones corresponding to adjacent visual zones are significant, the introduction of transition colors can create a natural spatial gradient in the lighting effect, thereby enhancing the overall sense and continuity of light and shadow within the vehicle.

[0090] As mentioned earlier, in addition to color, optical parameters also include brightness, frequency of change, etc. These parameters can be determined based on state data and / or subject audio.

[0091] In some embodiments, state data may be acquired, including at least one of occupant state data, vehicle state data, and environmental state data; based on the state data, the current scenario of the occupant may be determined, wherein the current scenario includes one of a driving scenario, an entertainment scenario, a rest scenario, and a warning scenario; and based on the current scenario, the optical parameters of lighting devices in at least one preset zone may be determined, wherein the preset zone includes at least one of an IP zone, a DP zone, and a Roof zone.

[0092] Occupant status data can include information such as facial expressions, eye-closing status, and head posture captured by in-vehicle cameras, as well as information such as occupant sitting posture and body movement detected by seat sensors, used to determine whether the occupant is focused on driving, relaxed, or excitedly engaging in entertainment. Vehicle status data can include vehicle speed, gear position, turn signal status, brake status, navigation information, etc., used to determine whether the vehicle is currently traveling at high speed or parked. Environmental status data can include time information (day / night), weather information (sunny / rainy), light intensity, and road condition information obtained through navigation, used to determine the environmental conditions in which the vehicle is located.

[0093] Based on the aforementioned status data, the current scenario of the occupants can be comprehensively determined. For example, when the vehicle is in motion at a high speed and / or the occupants' facial expressions are focused, it can be identified as a driving scenario. When the vehicle is parked, the occupants' facial expressions are relaxed or their eyes are closed, and / or the seat backs are reclined, it can be identified as a resting scenario. When the vehicle is in motion or parked, the occupants' facial expressions are pleasant, and / or music is playing inside the vehicle, it can be identified as an entertainment scenario. When the vehicle detects emergency braking, collision risk, or lane departure, it can be identified as a warning scenario.

[0094] Then, the optical parameters of the preset zones can be determined. Unlike the visual zones described above, which are based on the occupant's eye position, preset zones are fixed areas defined by the actual structural layout of the vehicle and are not directly related to the occupant's field of vision. The reason for using preset zones instead of visual zones when adjusting based on state data is that the scenarios reflected by the state data are often closely related to the functional positioning of specific structural areas within the vehicle. For example, driving scenarios require controlling the brightness of the IP area to avoid interfering with the driver's vision; resting scenarios focus more on the lighting comfort of the Roof area; and warning scenarios typically convey warning information through flashing across all areas. Visual zones, because they dynamically change with the occupant's eye position, cannot directly correspond to the functional needs of these fixed structural areas. Therefore, adjusting optical parameters based on preset zones can more directly respond to the differentiated control needs in different scenarios, complementing the control of visual zones.

[0095] For example, in a driving scenario, the dynamic effect of the lighting equipment in the IP area is determined to be constant brightness or slight brightness changes, while the dynamic effect of the lighting equipment in the DP and Roof areas is determined to be slow brightness changes. Alternatively, in an entertainment scenario, the dynamic effect of the lighting equipment in the DP, IP, and Roof areas is determined to be rapid and synchronized brightness changes. Alternatively, in a rest scenario, the dynamic effect of the lighting equipment in the Roof area is determined to be slow brightness changes, while the dynamic effect of the lighting equipment in the IP and DP areas is determined to be constant low brightness. Alternatively, in a warning scenario, the color of the lighting equipment in the IP, DP, and Roof areas is determined to be red or yellow, and the dynamic effect is a large and rapid change in brightness.

[0096] In other embodiments, a theme audio can be obtained; and based on the sound effect information of the theme audio, the optical parameters of the lighting equipment for the preset zone can be determined.

[0097] For example, thematic audio can be generated by an audio generation model based on occupant input, where the input includes at least one of speech, touch signals, and facial capture images. The audio generation model can be a deep learning model built on AI technology, capable of generating matching audio content based on input text descriptions, voice commands, touch signals, or emotional information. Common audio generation models include audio generation networks based on diffusion models or variational autoencoders.

[0098] Occupant input can include at least one of voice, touch signals, or facial capture images. For example, an occupant can describe "soothing piano music" or "dynamic electronic music" via voice. After receiving the voice command, the system converts it into a text description, which is then used by the audio generation model to generate the corresponding theme audio. Touch signals can come from the central control screen or the occupant's mobile device. The occupant selects the music style, rhythm type, or inputs keywords through touch operations, and the system uses this touch interaction information as the basis for generation. Facial capture images are obtained by capturing the occupant's facial information through an in-vehicle camera, identifying facial features, emotional states, etc., which are then used as reference factors when the audio generation model generates theme audio.

[0099] Besides being generated through audio generation models, thematic audio can also be obtained in various other ways. For example, occupants can directly upload audio files stored on mobile devices or in-vehicle storage; they can also play online streaming music through the in-vehicle media system; or they can use the in-vehicle microphone to capture occupants humming or speaking as thematic audio.

[0100] After obtaining the theme audio, its sound effect information can be extracted, including rhythm, volume, pitch, and spectral characteristics. Spectral characteristics refer to the energy distribution of the audio signal across different frequency ranges, such as the intensity of the low-frequency (20-200Hz), mid-frequency (200-2000Hz), and high-frequency (2000-20000Hz) bands. Based on this sound effect information, the optical parameters of the lighting equipment in the preset zones can be determined. For example, the flashing frequency of the lights can be controlled according to the rhythm frequency of the audio, the brightness of the lights can be controlled according to the volume of the audio, and the color change of the lights can be controlled according to the pitch of the audio. Furthermore, the energy distribution of different frequency ranges can be mapped to different areas based on the spectral characteristics of the audio. For example, low-frequency energy can be mapped to the lighting equipment in the footwell area, causing it to flash in sync with the bass rhythm; mid-frequency energy can be mapped to the lighting equipment in the DP area, causing it to change with human voices or instrument sounds; and high-frequency energy can be mapped to the lighting equipment in the Roof area, causing it to fluctuate with the treble frequencies. In this way, the lighting effects are linked to the audio content, creating an immersive audiovisual experience.

[0101] After the optical parameters of the lighting device are determined, control steps can be performed. In some embodiments, method 100 may further include: controlling the lighting device based on the determined optical parameters, wherein controlling the lighting device includes: controlling a first group of visual zones in the lighting device via a first communication link; controlling a second group of visual zones in the lighting device via a second communication link, wherein the visual priority of the first group is higher than that of the second group, and wherein the first communication link provides an independent link for each visual zone in the first group, and the second communication link provides a shared link for all visual zones in the second group.

[0102] The first group of visual zones can include core areas within the occupant's field of vision, such as the IP area directly in front of the driver. These areas require high response speed and smoothness of lighting, especially in dynamic lighting effects (such as those that move with music or change with images), necessitating high frame rates and low latency control to eliminate ghosting and stuttering. Therefore, each visual zone in the first group can be assigned an independent communication link to ensure that lighting control commands for each zone can be transmitted in real time and independently, without interference.

[0103] The second group of visual zones can include secondary areas within the occupant's field of vision, such as the DP area, footwell area, and roof area. These areas have relatively lower requirements for real-time lighting response. Therefore, all visual zones in the second group share the same communication link, transmitting control commands via time-division multiplexing or broadcasting to save communication resources and hardware costs.

[0104] In some embodiments, the first and second communication links can be communication links based on the vehicle's Controller Area Network (CAN), such as CAN FD (CAN with Flexible Data-Rate) links. CAN FD is an upgraded version of the traditional CAN protocol, supporting higher data transmission rates and larger data payloads, and can meet the communication requirements of in-vehicle lighting systems for multi-node, high-bandwidth, and real-time control.

[0105] To further reduce communication bandwidth consumption and improve control efficiency, frame compression processing can be performed on the transmitted optical parameter data in some embodiments. For example, for optical parameters in multiple consecutive frames, if the parameter changes between adjacent frames are small, only the changed frames or the difference data between frames can be transmitted, instead of transmitting all parameters frame by frame. Frame compression can effectively reduce the amount of data on the communication link while ensuring the continuous and smooth lighting effect.

[0106] For the purpose of non-restrictive description, Figure 4 This is a flowchart illustrating a non-limiting example process 200 in which a control method for cabin lighting equipment according to some embodiments of the present disclosure is applied. Figure 4 As shown, process 200 includes steps S202 to S218.

[0107] In step S202, the lighting device is divided into multiple visual zones. In step S204, a subject image is obtained. Then, in step S206, the subject image is divided into multiple image zones. After obtaining the dual zones (visual zones and image zones), the process proceeds to step S208, where the optical parameters of the lighting device for the multiple visual zones are determined based on the multiple image zones, for example, the color of the lighting device is determined.

[0108] In step S210, state data is obtained synchronously or asynchronously with steps S202 to S208. Then, in step S212, the current scene is determined based on the state data. Subsequently, in step S214, the optical parameters of the lighting equipment in the preset zones can be determined based on the current scene, for example, the brightness and / or variation frequency of the lighting equipment.

[0109] Alternatively or additionally, step S216 can be performed to obtain the theme audio. In this way, in step S214, the optical parameters of the lighting equipment in the preset zone can be determined based on the theme audio.

[0110] Finally, in step S218, the lighting equipment is controlled based on the determined optical parameters.

[0111] On the other hand, this disclosure provides a vehicle 300. For example... Figure 5As shown, vehicle 300 includes interior lighting equipment 301 and controller 304. Controller 304 is configured to perform the aforementioned control method for interior lighting equipment.

[0112] In another aspect, this disclosure provides a control system 400 for cabin lighting equipment. For example... Figure 6 As shown, system 400 includes external input device 420, domain controller 440, and execution module 460. System 400 can be installed inside a vehicle.

[0113] External input device 420 may include one or more of voice acquisition unit 422, touch acquisition unit 424, and image acquisition unit 426. In some embodiments, external input device 420 may also include other components such as gesture recognition sensors and physical buttons to acquire occupant input.

[0114] Domain controller 440 may include a communication unit 442 and a multimodal data processing unit 444. The multimodal data processing unit 444 may be configured to execute the aforementioned control method for cabin lighting equipment. Communication unit 442 may be configured to communicate with cloud processing module 500 (including generative unit 520), external input device 420, and execution module 460, respectively. Input collected by external input device 420 may be transmitted to cloud processing module 500 via communication unit 442. Thematic images and / or thematic audio generated by generative unit 520 based on this input may be transmitted back to the domain controller, enabling multimodal data processing unit 444 to determine the optical parameters of the lighting equipment based on the thematic image, thematic audio, and / or the collected input.

[0115] The execution module 460 may include a light controller 462 and a lighting device 464. The light controller 462 can receive optical parameters transmitted by the communication unit 442 to control the lighting device 464.

[0116] Various embodiments of vehicle 300 and system 400 can be referred to similarly to the previous description of method 100, and will not be repeated here.

[0117] This disclosure also provides a computing device that may include one or more processors and a memory storing computer-executable instructions, which, when executed by the one or more processors, cause the one or more processors to perform the methods described according to any of the foregoing embodiments of this disclosure. Figure 7As shown, computing device 600 may include one or more processors 602 and memory 604 storing computer-executable instructions that, when executed by one or more processors 602, cause one or more processors 602 to perform the methods described according to any of the foregoing embodiments of this disclosure. The one or more processors 602 may be, for example, a central processing unit (CPU) of computing device 600. The one or more processors 602 may be any type of general-purpose processor, or may be a processor specifically designed for the control of cabin lighting equipment, such as an application-specific integrated circuit (“ASIC”). Memory 604 may be coupled to one or more processors 602 and may include various computer-readable media accessible by one or more processors 602. In various embodiments, memory 604 described herein may include volatile and non-volatile media, removable and non-removable media. For example, memory 604 may include any combination of random access memory (“RAM”), dynamic RAM (“DRAM”), static RAM (“SRAM”), read-only memory (“ROM”), flash memory, cache memory, and / or any other type of non-transient computer-readable media. The memory 604 may store instructions that, when executed by the processor 602, cause the processor 602 to execute the method described according to any of the foregoing embodiments of the present disclosure.

[0118] This disclosure also provides a computer-readable storage medium having computer-executable instructions stored thereon, which, when executed by a computer, cause the computer to perform the methods described according to any of the foregoing embodiments of this disclosure.

[0119] This disclosure also provides a computer program product that may include instructions that, when executed by a processor, can implement the methods described according to any of the foregoing embodiments of this disclosure. The instructions may be any set of instructions that will be executed directly by one or more processors, such as machine code, or any set of instructions that will be executed indirectly, such as a script. The instructions may be stored in an object code format for direct processing by one or more processors, or stored in any other computer language, including scripts or sets of independent source code modules that are interpreted on demand or compiled in advance.

[0120] Figure 8This is a schematic block diagram illustrating a computer system 700 on which embodiments of the present disclosure may be implemented. The computer system 700 includes a bus 702 or other communication mechanism for transmitting information, and a processing means 704 coupled to the bus 702 for processing information. The computer system 700 also includes a memory 706 coupled to the bus 702 for storing instructions to be executed by the processing means 704. The memory 706 may be random access memory (RAM) or other dynamic storage device. The memory 706 may also be used to store temporary variables or other intermediate information during the execution of instructions to be executed by the processing means 704. The computer system 700 also includes a read-only memory (ROM) 708 or other static storage device coupled to the bus 702 for storing static information and instructions for the processing means 704. A storage device 710, such as a magnetic disk or optical disk, is provided and coupled to the bus 702 for storing information and instructions. Computer system 700 may be coupled via bus 702 to output device 712 for providing output to a user, such as, but not limited to, a display (e.g., a cathode ray tube (CRT) or liquid crystal display (LCD)), speakers, etc. Input device 714, such as a keyboard, mouse, microphone, etc., is coupled to bus 702 for transmitting information and command selections to processing device 704. Computer system 700 may perform embodiments of this disclosure. Consistent with certain implementations of this disclosure, results are provided by computer system 700 in response to processing device 704 executing one or more sequences of one or more instructions contained in memory 706. Such instructions may be read into memory 706 from another computer-readable medium, such as storage device 710. Execution of the sequence of instructions contained in memory 706 causes processing device 704 to perform the methods described herein. Alternatively, the teachings may be implemented using a hard-wired circuit system instead of or in combination with software instructions. Therefore, implementations of this disclosure are not limited to any particular combination of hardware circuit systems and software. In various embodiments, computer system 700 can be connected across a network to one or more other computer systems, such as computer system 700, to form a networked system via network interface 716. This network may include a private network or a public network such as the Internet. In a networked system, one or more computer systems can store data and supply data to other computer systems. As used herein, the term "computer-readable medium" refers to any medium that participates in providing instructions to processing device 704 for execution. Such media can take many forms, including but not limited to non-volatile media, volatile media, and transmission media. Non-volatile media include, for example, optical discs or magnetic disks such as storage device 710. Volatile media include dynamic memory such as memory 706. Transmission media include coaxial cables, copper wires, and optical fibers, including wiring containing bus 702.Common forms of computer-readable media or computer program products include, for example, floppy disks, flexible disks, hard disks, magnetic tapes, or any other magnetic media, CD-ROMs, digital video discs (DVDs), Blu-ray discs, any other optical media, thumb drives, memory cards, RAM, PROMs and EPROMs, fast EPROMs, any other memory chips or cartridges, or any other tangible media from which a computer can read. Various forms of computer-readable media may be involved when carrying one or more sequences of one or more instructions to processing device 704 for execution. For example, instructions may initially be carried on a disk of a remote computer. The remote computer may load the instructions into its dynamic memory and transmit the instructions over a telephone line using a modem. A modem local to computer system 700 may receive data over a telephone line and convert the data into an infrared signal using an infrared transmitter. An infrared detector coupled to bus 702 may receive the data carried in the infrared signal and place the data on bus 702. Bus 702 carries the data to memory 706, from which processing device 704 retrieves and executes the instructions. Optionally, the instructions received by the memory 706 may be stored on the storage device 710 before or after execution by the processing device 704.

[0121] According to various embodiments, instructions configured to be executed by a processing device to perform a method are stored on a computer-readable medium. The computer-readable medium may be a device for storing digital information. For example, a computer-readable medium includes a compact disc read-only memory (CD-ROM) as known in the art for storing software. The computer-readable medium is accessed by a processor adapted to execute the instructions configured to be executed.

[0122] The foregoing has described one or more exemplary embodiments of this disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0123] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or physical entities, or by products with certain functions. A typical implementation device is a server system. Of course, this disclosure does not exclude the possibility that, with the future development of computer technology, the computer implementing the functions of the above embodiments may be, for example, a personal computer, a laptop computer, an in-vehicle human-machine interaction device, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a game console, a tablet computer, a wearable device, or any combination thereof.

[0124] The terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, product, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, product, or apparatus. Without further limitation, the presence of other identical or equivalent elements in the process, method, product, or apparatus that includes said elements is not excluded. For example, the use of terms such as "first" or "second" to denote names does not indicate any particular order.

[0125] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, when implementing one or more embodiments of this disclosure, the functions of each module can be implemented in one or more software and / or hardware, or a module that performs the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0126] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more blocks of the flowchart illustrations and / or one or more blocks of the block diagrams.

[0127] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0128] Those skilled in the art will understand that one or more embodiments of this disclosure may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, one or more embodiments of this disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0129] One or more embodiments of this disclosure can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a particular task or implement a particular abstract data type. One or more embodiments of this disclosure can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules can reside in local and remote computer storage media, including storage devices.

[0130] The same or similar parts between the various embodiments of this disclosure can be referred to mutually, and each embodiment focuses on describing the differences from other embodiments. In particular, for the apparatus embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and relevant parts can be referred to the description of the method embodiments. In the description of this disclosure, the reference to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," "exemplary," etc., means that the specific feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of this disclosure. In this disclosure, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this disclosure and the features of different embodiments or examples.

[0131] Additionally, when used in this disclosure, the terms “here,” “above,” “below,” “below,” “in the following,” “overall,” and similar terms should refer to the entirety of this disclosure and not any particular part thereof. Furthermore, unless expressly stated otherwise or otherwise understood in the context in which they are used, conditional language used herein, such as “may,” “possibly,” “for example,” “like,” etc., is generally intended to express that certain embodiments include, while other embodiments do not, certain features, elements, and / or states. Therefore, such conditional language is not generally intended to imply that one or more embodiments require features, elements, and / or states in any way, or whether such features, elements, and / or states are included or performed in any particular embodiment.

[0132] The above description is merely an embodiment of one or more embodiments of this disclosure and is not intended to limit the scope of the one or more embodiments of this disclosure. Various modifications and variations can be made to the one or more embodiments of this disclosure by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the scope of the claims.

Claims

1. A control method for cabin lighting equipment, characterized in that, The method includes: Based on the occupant's head position or eye position, the lighting equipment is dynamically divided into multiple visual zones, where different occupant head positions or eye positions correspond to different visual zone division results. Obtain the subject image; An image semantic recognition model is used to perform image semantic recognition on the subject image to obtain multiple semantic regions; Based on the multiple semantic regions and the preset visual cognitive hierarchy, the theme image is divided into multiple image partitions, such that each image partition and each visual partition have an associated spatial correspondence in the occupant's field of vision; and Based on the image information of each image partition and the spatial correspondence, the optical parameters of the lighting equipment for each visual partition are determined. The plurality of visual partitions are distributed along a first direction, and dividing the subject image into a plurality of image partitions includes: merging and sorting the plurality of semantic regions according to the visual cognitive hierarchy to obtain the plurality of image partitions corresponding to each level in the visual cognitive hierarchy. The number of the plurality of image partitions corresponds to the number of the plurality of visual partitions, and the order of each image partition along the first direction corresponds to the distribution order of each visual partition in the occupant's field of vision.

2. The method according to claim 1, characterized in that, Dividing the subject image into multiple image partitions includes: The subject image is divided into multiple image partitions along the first direction, and the number of the multiple image partitions corresponds to the number of the multiple visual partitions.

3. The method according to claim 2, characterized in that, Dividing the subject image into multiple image partitions includes: Adjust the size of each image partition along the first direction so that the size is proportional to the number of illumination units in the corresponding visual partition.

4. The method according to claim 1, characterized in that, Based on the image information of each image partition and the spatial correspondence, the optical parameters of the lighting device for each visual partition are determined, including: Extract candidate colors from each image partition and calculate the color proportion of each candidate color in that image partition; Select at least twice from the candidate colors to generate multiple color combinations, each color combination including at least two of the candidate colors; The combination proportion of each color combination in the image partition is calculated based on the color proportion, and the hue difference between the candidate colors within each color combination is calculated, thereby determining the target color combination from the plurality of color combinations based on the combination proportion and the hue difference; and The color of the lighting device for the visual zone corresponding to the image zone is determined based on the target color combination.

5. The method according to claim 4, characterized in that, Extracting candidate colors from the image partitions includes: Extract multiple colors from the image partitions in the HSV color space of the subject image; and Colors with brightness values ​​below a brightness threshold are filtered out, and the remaining colors are used as candidate colors.

6. The method according to claim 4, characterized in that, Based on the image information of each image partition and the spatial correspondence, determining the optical parameters of the lighting device for each visual partition further includes: Obtain the target color combination of two adjacent visual zones; Determine whether the color parameter difference between the two target color combinations exceeds a color parameter difference threshold; If the color parameter difference exceeds a color parameter difference threshold, a transitional color sequence is generated that gradually changes from one target color combination to another; and Based on the transition color sequence, the colors of at least a portion of the lighting devices in the two adjacent visual zones are determined to make the colors of the two adjacent visual zones transition smoothly.

7. The method according to claim 1, characterized in that: The subject image is generated using an image generation model based on the occupant's input, wherein the input includes at least one of voice, touch signals, and facial capture images.

8. The method according to claim 1, characterized in that, The method further includes: Obtain status data, which includes at least one of occupant status data, vehicle status data, and environmental status data; Based on the state data, the occupant's current scenario is determined, wherein the current scenario includes one of a driving scenario, an entertainment scenario, a rest scenario, and a warning scenario; and Based on the current scenario, determine the optical parameters of the lighting equipment in at least one preset zone, wherein the preset zone includes at least one of the dashboard area, door panel area, and ceiling area.

9. The method according to claim 1, characterized in that, The method further includes: Get the theme audio; and Based on the sound effect information of the theme audio, the optical parameters of the lighting equipment in the preset zone are determined.

10. The method according to claim 9, characterized in that: The subject audio is generated by an audio generation model based on occupant input, wherein the input includes at least one of speech, touch signals, and facial capture images.

11. The method according to any one of claims 1 to 10, characterized in that, The method further includes controlling the lighting device based on the determined optical parameters, wherein controlling the lighting device includes: The first group of visual zones in the lighting device is controlled via a first communication link; The second set of visual zones in the lighting device is controlled via a second communication link. Among them, the visual priority of the first group is higher than that of the second group, and The first communication link provides an independent link for each visual partition in the first group, while the second communication link provides a shared link for all visual partitions in the second group.

12. The method according to claim 11, characterized in that: The first set of visual partitions includes the dashboard area; The second set of visual zones includes the door panel area and the ceiling area; and The first communication link and the second communication link are communication links based on the vehicle's controller local area network.

13. A vehicle, characterized in that, The vehicles include: Interior lighting equipment; and The controller is configured to perform the method according to any one of claims 1 to 12.

14. A control system for cabin lighting equipment, characterized in that, The system includes: An external input device, including at least one of a voice acquisition unit, a touch acquisition unit, and an image acquisition unit; A domain controller, including a communication unit and a multimodal data processing unit, the multimodal data processing unit being configured to perform the method according to any one of claims 1 to 12; and The execution module includes a light controller and lighting equipment. The communication unit is configured to communicate with the cloud processing module including the generative unit, the external input device, and the execution module, respectively.

15. A computing device, characterized in that, The computing device includes: One or more processors; and A memory storing computer-executable instructions, which, when executed by the one or more processors, cause the one or more processors to perform the method according to any one of claims 1 to 12.

16. A computer-readable storage medium having computer-executable instructions stored thereon, characterized in that, The computer-executable instructions, when executed by a computer, cause the computer to perform the method according to any one of claims 1 to 12.

17. A computer program product, characterized in that, The computer program product includes instructions that, when executed by a processor, implement the method according to any one of claims 1 to 12.

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