Self-adaptive projection method and device, electronic equipment and storage medium

Abstract

The invention provides a self-adaptive projection method and device, electronic equipment and a storage medium, and relates to the technical field of vehicles, and the method comprises the steps: obtaining ground environment data of a to-be-projected region; ground environment analysis is conducted on the ground environment data, an environment analysis result is obtained, and the environment analysis result comprises at least one of ground flatness, ground texture, ground roughness and ground materials; and adjusting a projection strategy according to the environment analysis result so as to improve the projection effect.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and more specifically, to an adaptive projection method, device, electronic device, and storage medium. Background Technology

[0002] The main function of the ground lights on a vehicle is to illuminate the ground area near the door in low-light conditions, so as to help passengers accurately identify their footing position, thereby improving safety and convenience during the process of getting on and off the vehicle.

[0003] Ground lights are typically fixed in place on vehicle sills or below doors. However, since the projection angle and position of ground lights are fixed after installation, the original projection area may shift or deform when the ground environment changes, resulting in poor projection effects.

[0004] In related technologies, a manual adjustment mechanism is used to correct the projection angle of the ground lights. This type of solution can only adjust the initial installation angle of the lights within a limited range and cannot dynamically adapt to real-time changes in the external environment. Especially in complex or non-standard parking scenarios, manual adjustment is difficult to accurately match the actual ground conditions, resulting in a significant deficiency in the projection effect of the ground lights. Summary of the Invention

[0005] The problem this invention addresses is how to improve projection effects.

[0006] To address the above problems, the present invention provides an adaptive projection method, apparatus, electronic device, and storage medium.

[0007] In a first aspect, the present invention provides an adaptive projection method, comprising: Acquire ground environment data of the area to be projected; The ground environment data is analyzed to obtain environmental analysis results, wherein the environmental analysis results include at least one of ground flatness, ground texture, ground roughness, and ground material. Adjust the projection strategy based on the environmental analysis results.

[0008] Optionally, adjusting the projection strategy based on the environmental analysis results includes: Sub-regions are obtained by segmenting the region to be projected; The projection strategy for the sub-region is adjusted based on the environmental analysis results of the sub-region.

[0009] Optionally, the ground environment data includes point cloud data; the step of performing ground environment analysis on the ground environment data to obtain the environment analysis results includes: The curvature of the point cloud data is obtained by fitting the point cloud data with a second-order polynomial model. The surface roughness is determined based on the value of the curvature, and the edge contour is determined based on the change of the curvature. The flatness of the ground is determined based on the curvature, the surface roughness, and the edge profile.

[0010] Optionally, the ground environment data includes polarization data of the area to be projected; the step of performing ground environment analysis on the ground environment data to obtain the environment analysis results further includes: The ground texture is obtained by processing the polarization data of the area to be projected using a convolutional neural network.

[0011] Optionally, the ground environment data includes electromagnetic wave time-domain data; the step of performing ground environment analysis on the ground environment data to obtain the environmental analysis results further includes: The electromagnetic wave time-domain data is converted into frequency-domain data using a fast Fourier transform. The ground roughness corresponding to the frequency domain data is determined according to the preset roughness frequency domain mapping relationship.

[0012] Optionally, the ground environment data further includes temperature data and reflectivity data; the step of performing ground environment analysis on the ground environment data to obtain the environmental analysis results further includes: Based on the preset mapping relationship between temperature, reflectivity, and material, the ground material corresponding to the temperature data and the reflectivity data is determined.

[0013] Optionally, adjusting the projection strategy based on the environmental analysis results includes: The elevation difference is compensated according to the flatness of the ground, the intensity of the projected light is adjusted according to the texture and / or roughness of the ground, the projection angle is adjusted according to the roughness of the ground, and the color of the projected light source is adjusted according to the material of the ground.

[0014] In a second aspect, the present invention provides an adaptive projection device, comprising: The data acquisition module is used to acquire ground environment data of the area to be projected. The environmental analysis module is used to perform ground environment analysis on the ground environment data to obtain environmental analysis results, wherein the environmental analysis results include at least one of ground flatness, ground texture, ground roughness, and ground material. The strategy adjustment module is used to adjust the projection strategy based on the environmental analysis results.

[0015] Thirdly, the present invention provides an electronic device, including a memory and a processor; The memory is used to store computer programs; The processor is configured to implement the adaptive projection method as described in the first aspect when executing the computer program.

[0016] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the adaptive projection method as described in the first aspect.

[0017] The beneficial effects of the adaptive projection method of the present invention are: By acquiring ground environment data of the area to be projected, the actual physical state of the ground is determined. Ground environment data is then analyzed to obtain environmental analysis results. Ground flatness reflects surface undulation characteristics and is used to optimize elevation difference compensation values ​​and eliminate projection distortion caused by ground unevenness. Ground roughness reflects the scattering ability of the microstructure and is used to adjust the degree of beam defocusing and suppress reflection interference from smooth surfaces. Ground material reflects surface reflectivity and is used to determine the light source color to avoid color conflicts with the ground. Ground texture reflects the pattern reflection mode and is used to set the light intensity to prevent excessive brightness or darkness. Based on the environmental analysis results, the projection strategy is adjusted to match the projection parameters to the ground characteristics, reducing distortion, reflection interference, and brightness imbalance, thereby improving the clarity and stability of the projected image and ultimately enhancing the projection effect. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the adaptive projection method according to an embodiment of the present invention; Figure 2 This is a flowchart of the adaptive projection method according to an embodiment of the present invention; Figure 3 This is an example diagram of the adaptive projection device according to an embodiment of the present invention; Figure 4 This is an example diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0019] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the accompanying drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0020] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0021] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to"; the term "based on" means "at least partially based on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; and the term "optionally" means "optional embodiments". Definitions of other terms will be given in the following description. It should be noted that the concepts of "first," "second," etc., mentioned in this invention are used only to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0022] It should be noted that the terms "a" and "a plurality of" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0023] The names of the messages or information exchanged between the multiple devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0024] like Figure 1 As shown, an adaptive projection method provided in this embodiment of the invention includes: Step S100: Obtain ground environment data of the area to be projected.

[0025] The area to be projected represents the area that the ground illumination lamp can project onto. The ground environment data represents data that may affect the projection effect of the ground illumination lamp. By analyzing the ground environment data of the area to be projected, targeted adjustments can be made to the ground in that area to improve the projection effect of the ground illumination lamp.

[0026] In one embodiment, ground environment data of the area to be projected is acquired through sensing devices mounted on the vehicle. For example, the ground environment can be identified from multiple dimensions using 3D laser scanners, polarization cameras, millimeter-wave radar, and thermal imaging sensors. This can solve the problem of misidentification caused by single-dimensional sensors and also enable accurate identification of complex ground environment data.

[0027] Step S200: Perform ground environment analysis on the ground environment data to obtain environmental analysis results, wherein the environmental analysis results include at least one of ground flatness, ground texture, ground roughness, and ground material.

[0028] Ground smoothness is used to characterize the degree of undulation of the ground surface. Its value reflects the undulation characteristics of the ground. For example, cobblestone ground has low smoothness, while waterlogged ground has high smoothness.

[0029] Ground roughness is used to characterize the differences in the microstructure of the ground surface. Its value reflects the surface's scattering ability; for example, grass has a high value and ice has a low value.

[0030] Ground material is used to characterize the reflective properties and material type of the ground. Differences in its properties reflect the intensity of reflection; for example, snow has high reflectivity, while ceramic tiles have medium reflectivity.

[0031] Ground texture is used to characterize the pattern features of the ground surface. Its pattern changes reflect the reflection pattern, such as water appearing as ripples and ice appearing as a smooth surface.

[0032] Step S300: Adjust the projection strategy based on the environmental analysis results.

[0033] Based on the dynamically configured combination of projection parameters according to the ground environment analysis results, a suitable projection strategy is determined, including factors such as light intensity, elevation difference compensation, beam defocusing degree, and light source color. By adjusting the projection strategy according to the environmental analysis results, ground characteristics can be transformed into a basis for real-time adjustment of projection parameters. This suppresses projection distortion caused by ground undulations, reduces reflection interference from smooth surfaces, optimizes brightness to adapt to material reflection characteristics, and improves projection clarity and environmental adaptability. It is suitable for diverse ground conditions such as pebbles, grass, and ice surfaces, achieving stable and reliable projection effects.

[0034] In this embodiment, the actual physical state of the ground is determined by acquiring ground environment data of the area to be projected. Ground environment data is then analyzed to obtain environmental analysis results. Ground flatness reflects surface undulation characteristics and is used to optimize elevation difference compensation values ​​and eliminate projection distortion caused by ground unevenness. Ground roughness reflects the scattering ability of the microstructure and is used to adjust the degree of beam defocusing and suppress reflection interference from smooth surfaces. Ground material reflects surface reflection characteristics and is used to determine the light source color to avoid conflict with the ground color. Ground texture reflects the pattern reflection mode and is used to set the light intensity to prevent excessive brightness or darkness. Based on the environmental analysis results, the projection strategy is adjusted to match the projection parameters with the ground characteristics, reducing distortion, reflection interference, and brightness imbalance, thereby improving the clarity and stability of the projected image.

[0035] Optionally, adjusting the projection strategy based on the environmental analysis results includes: Sub-regions are obtained by segmenting the region to be projected; The projection strategy for the sub-region is adjusted based on the environmental analysis results of the sub-region.

[0036] In one embodiment, the area to be projected is divided into multiple sub-regions, the ground environment of each sub-region is analyzed separately, and the projection strategy of the corresponding sub-region is adjusted according to the environmental analysis results of each sub-region to further improve the projection effect.

[0037] Specifically, by using adjustable optical elements and a spatial light modulator, projection parameters such as brightness and reflection angle are independently set for each sub-region to achieve adaptive projection for different sub-regions. For example, if sub-region 1 is a water accumulation area and sub-region 2 is a pebble area, then the brightness of sub-region 1 is reduced and the projection angle of sub-region 1 is adjusted to avoid reflections; the brightness of sub-region 2 does not need to be adjusted, but the pebble area has a more complex elevation difference, so elevation difference compensation is performed on sub-region 2 to reduce pattern distortion caused by uneven ground.

[0038] Optionally, the ground environment data includes point cloud data; the step of performing ground environment analysis on the ground environment data to obtain the environment analysis results includes: The curvature of the point cloud data is obtained by fitting the point cloud data with a second-order polynomial model.

[0039] The surface roughness is determined based on the value of the curvature, and the edge contour is determined based on the change of the curvature.

[0040] The flatness of the ground is determined based on the curvature, the surface roughness, and the edge profile.

[0041] In one embodiment, point cloud data of the area to be projected, i.e., the three-dimensional coordinate points of the surface of the area to be projected, is acquired using a 3D laser scanner. Within the area to be projected or a sub-area, a second-order polynomial is used to fit the point cloud data. The coefficients to be fitted are solved using the least squares method to minimize the error between the fitted surface and the actual point cloud data. After completing the second-order polynomial fitting, the curvature of the fitted surface is calculated.

[0042] For example, curvature is calculated based on the Hessian matrix of the fitted surface, thus obtaining Gaussian curvature and mean curvature. The surface convexity / concavity is determined by the curvature value; for instance, when curvature K > 0, the surface is convex or concave at that point; when K < 0, the surface is saddle-shaped at that point; and when K = 0, the surface may be cylindrical, conical, or planar at that point. A curvature change threshold is set; when the curvature change exceeds the threshold, it is determined to be an edge contour.

[0043] When the standard deviation of curvature is greater than the standard deviation threshold, and the absolute value of the average curvature is less than the preset average value (i.e., close to 0), and there are multiple local curvature peaks, the current ground is determined to be a cobblestone ground; when the standard deviation of curvature is less than the standard deviation threshold, and the average curvature is less than 0, and the curvature change is smooth without obvious peaks, the current ground is determined to be a waterlogged ground.

[0044] Optionally, the ground environment data includes polarization data of the area to be projected; the step of performing ground environment analysis on the ground environment data to obtain the environment analysis results further includes: The ground texture is obtained by processing the polarization data of the area to be projected using a convolutional neural network.

[0045] In one embodiment, polarization data of the area to be projected is acquired using a polarization camera to capture the polarization state of light waves. A convolutional neural network is trained using polarization data from different ground environments as a training set to obtain a classification model based on the convolutional neural network. The acquired polarization data is processed to obtain ground texture features. For example, the polarization state of light waves in the area to be projected is analyzed using a convolutional neural network, and the texture uniformity or classification result is determined based on the polarization angle and degree of polarization in the polarization state.

[0046] For example, a trained convolutional neural network is used to process the degree of polarization and the polarization angle to obtain texture uniformity and classification results. If the degree of polarization is higher than the second preset polarization threshold, the polarization angle has no obvious pattern, and the texture uniformity is uniform, the classification result is ice surface; if the degree of polarization is higher than the first preset polarization threshold but lower than the second preset polarization threshold, and the texture is a regular grid texture, the classification result is tile; if the degree of polarization is higher than the second preset polarization threshold, the polarization angle direction is consistent, and the texture has no obvious pattern, the classification result is water accumulation.

[0047] Optionally, the ground environment data includes electromagnetic wave time-domain data; the step of performing ground environment analysis on the ground environment data to obtain the environmental analysis results further includes: The electromagnetic wave time-domain data is converted into frequency-domain data using a fast Fourier transform.

[0048] The ground roughness corresponding to the frequency domain data is determined according to the preset roughness frequency domain mapping relationship.

[0049] In one embodiment, time-domain data of electromagnetic waves are acquired by millimeter-wave radar, including the amplitude of the echo signal, i.e., the intensity of the reflected electromagnetic wave received by the radar; the phase of the echo signal, i.e., the phase information of the reflected electromagnetic wave; and the time delay of the echo signal, i.e., the time difference from transmission to reception.

[0050] Ground surface roughness affects the spatial frequency distribution of reflected light. Therefore, after obtaining the time-domain signal, a Fast Fourier Transform (FFT) is used to convert it into a frequency-domain signal to analyze the impact of surface roughness on the spatial frequency distribution of reflected light. A pre-established roughness frequency-domain mapping relationship is used to determine the ground roughness corresponding to the frequency-domain data. This roughness frequency-domain mapping relationship is established experimentally or theoretically to correlate surface roughness parameters with the spectral characteristics of the FFT. Surface roughness parameters are then calculated based on these spectral characteristics, such as through arithmetic mean roughness or maximum height roughness.

[0051] Specifically, the frequency domain characteristics of different types of ground materials exhibit typical differences: For example, the surface of ice is smooth, and the reflection is mainly specular, with electromagnetic wave energy concentrated in the low-frequency region. This is manifested by the low-frequency component being significantly higher than the preset frequency domain threshold, and the high-frequency attenuation being rapid. The surface of grass and snow is rough and porous, and the reflection exhibits diffuse scattering characteristics. The energy is distributed over a wide frequency range, especially with strong high-frequency components that exceed the preset threshold. The surface of ceramic tiles is flat but has regular textures, and may simultaneously exhibit mid-to-low frequency dominance and periodic spectral peaks. The surface of water in stagnant water areas is smooth, similar to specular reflection, and also exhibits low-frequency dominance characteristics, but it needs to be combined with other sensors to distinguish water from ice. The surface of pebbles or gravel is highly irregular, with strong scattering, rich high-frequency components, and no obvious regularity in the spectrum.

[0052] Optionally, the ground environment data further includes temperature data and reflectivity data; the step of performing ground environment analysis on the ground environment data to obtain the environmental analysis results further includes: Based on the preset mapping relationship between temperature, reflectivity, and material, the ground material corresponding to the temperature data and the reflectivity data is determined.

[0053] In one embodiment, temperature field and reflectivity data of a known material ground are collected, with multiple sample points collected for each material to ensure statistical reliability. The temperature and reflectivity values ​​of each sample point are mapped into a matrix, and the distribution characteristics of each material in the temperature and reflectivity space are calculated to form a temperature-reflectivity matrix for each material, i.e., the mapping relationship between temperature, reflectivity, and material.

[0054] Temperature and reflectivity data of the area to be projected are collected using a thermal imaging sensor. The corresponding ground material is determined by mapping the temperature and reflectivity data to the material. This is primarily used to identify snow, ice, and ceramic tiles. For example, when the reflectivity is higher than a second reflectivity threshold and the temperature is below 0°C, the material is identified as ice; when the reflectivity is higher than a third reflectivity threshold and the temperature is below -5°C, the material is identified as snow; when the reflectivity is higher than a first reflectivity threshold but lower than a second reflectivity threshold and the temperature is close to ambient temperature, the material is identified as ceramic tile. Specifically, the first reflectivity threshold is lower than the second reflectivity threshold, and the second reflectivity threshold is lower than the third reflectivity threshold. In another embodiment, the material is determined by reflectivity, texture, and edges. For example, when high polarization reflection is detected, accompanied by dynamic texture changes and blurred edges, it is determined to be a water accumulation area; if the surface has a regular grid-like texture and medium reflectivity, it is determined to be a ceramic tile; when diffuse reflection characteristics, high reflectivity, and low temperature environment information are present, it is determined to be a grass or snow-covered area; a surface with high polarization reflection, concentrated reflected light energy, and medium to low temperature conditions is determined to be an ice surface; when radar or visual data reflects small height fluctuations and irregular contour structures, it is determined to be a cobblestone road surface.

[0055] Optionally, such as Figure 2 As shown, adjusting the projection strategy based on the environmental analysis results includes: The elevation difference is compensated according to the flatness of the ground, the intensity of the projected light is adjusted according to the texture and / or roughness of the ground, the projection angle is adjusted according to the roughness of the ground, and the color of the projected light source is adjusted according to the material of the ground.

[0056] In one embodiment, a spatial light modulator is used to independently set the optimal brightness for the projected area or sub-area on the projected image based on the identified terrain reflection characteristics and ambient light through pixel-level brightness control. Brightness is increased on textured or rough surfaces with high absorption, and decreased on surfaces with low absorption or low roughness. Elevation compensation is applied to uneven surfaces, while no processing is performed on smooth surfaces. Adjustable optical elements are used to achieve overall or partial beam adjustment; for example, dynamically adjusting the reflector surface using deformable mirrors allows for beam deflection, focusing, and defocusing to quickly adjust the projection angle and compensate for large-scale distortion. Light source control adjusts the light source color according to different terrains to make the projected light more conspicuous. Specifically, the system can compensate for elevation differences, adjust the intensity of projected light, adjust the projection angle, and adjust the color of the projected light source by considering ground flatness, ground texture, ground roughness, and ground material. It can also use a classifier to determine the ground type based on the ground flatness, ground texture, ground roughness, and ground material, and then compensate for elevation differences, adjust the intensity of projected light, adjust the projection angle, and adjust the color of the projected light source accordingly.

[0057] For example, a classifier can be used to determine the category of the area or sub-area to be projected, such as water, ice, grass, pebbles, snow, etc., and the projection strategy can be further determined based on the category. For waterlogged areas, brightness is reduced in high-reflectivity areas to suppress glare, while blue auxiliary light is projected in dark areas to enhance outline visibility. Adjustable optical elements are used to adjust the beam direction or polarization state to avoid specular reflections at specific viewing angles. In icy areas, the projection color temperature is increased, and a blue warning ring is superimposed to strengthen hazard warnings. Simultaneously, polarization control is used to prevent strong reflections from interfering with the driver's vision. In grassy or snowy areas, the red light component is enhanced to improve warmth and visibility. For snowy areas, the brightness and color temperature ratio can be further optimized by incorporating temperature information. In cobblestone areas, localized light intensity modulation is used to supplement light in recessed areas and moderately darken raised areas to eliminate projection distortion and shadow occlusion caused by uneven terrain, restoring the true terrain structure. In tiled areas, the proportion of blue light is reduced to avoid cool tones enhancing ground reflections. At the same time, red warning rings are superimposed in key locations to maintain visual comfort while increasing pedestrian or vehicle alertness to hard, smooth surfaces.

[0058] When the door is opened, the ground lights project onto the ground according to the projection strategy, so that different surfaces can achieve the best projection effect.

[0059] like Figure 3 As shown, an adaptive projection device provided in an embodiment of the present invention includes: The data acquisition module is used to acquire ground environment data of the area to be projected. The environmental analysis module is used to perform ground environment analysis on the ground environment data to obtain environmental analysis results, wherein the environmental analysis results include at least one of ground flatness, ground texture, ground roughness, and ground material. The strategy adjustment module is used to adjust the projection strategy based on the environmental analysis results.

[0060] like Figure 4 As shown, an electronic device 400 provided in this embodiment of the invention includes a memory 410 and a processor 420; the memory 410 is used to store a computer program; the processor 420 is used to implement the adaptive projection method as described above when the computer program is executed.

[0061] Alternatively, an electronic device 400 includes a memory 410 and a processor 420 coupled to the memory 410; the memory 410 is configured to store a computer program; and the processor 420 is configured to perform the following operations when the computer program is executed: Acquire ground environment data of the area to be projected; The ground environment data is analyzed to obtain environmental analysis results, wherein the environmental analysis results include at least one of ground flatness, ground texture, ground roughness, and ground material. Adjust the projection strategy based on the environmental analysis results.

[0062] This invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the adaptive projection method described above.

[0063] Alternatively, a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the following operations: Acquire ground environment data of the area to be projected; The ground environment data is analyzed to obtain environmental analysis results, wherein the environmental analysis results include at least one of ground flatness, ground texture, ground roughness, and ground material. Adjust the projection strategy based on the environmental analysis results.

[0064] The present invention will now be described an electronic device 400 that can serve as a server or client of the present invention, which is an example of a hardware device that can be applied to various aspects of the present invention. Electronic device 400 is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic device 400 can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0065] Electronic device 400 includes a computing unit that can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) or a computer program loaded from a storage unit into random access memory (RAM). The RAM may also store various programs and data required for device operation. The computing unit, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0066] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. In this application, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention according to actual needs. Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units can be implemented in hardware or as software functional units.

[0067] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A method of adaptive projection, characterized in that, The method comprises: acquiring ground environment data of a region to be projected; performing ground environment analysis on the ground environment data to obtain an environment analysis result, wherein the environment analysis result comprises at least one of ground flatness, ground texture, ground roughness, and ground material; adjusting a projection strategy according to the environment analysis result.

2. The adaptive projection method of claim 1, wherein, The adjusting of the projection strategy according to the environment analysis result comprises: obtaining a sub-region through segmentation of the region to be projected; adjusting the projection strategy for the sub-region according to the environment analysis result of the sub-region.

3. The adaptive projection method according to claim 1 or 2, characterized in that, The ground environment data comprises point cloud data; the performing of the ground environment analysis on the ground environment data to obtain an environment analysis result comprises: fitting the point cloud data through a second-order polynomial model to obtain a curvature corresponding to the point cloud data; determining surface concave-convexity according to a value of the curvature and determining an edge contour according to a change of the curvature; determining the ground flatness according to the curvature, the surface concave-convexity, and the edge contour.

4. The adaptive projection method of claim 1 or 2, wherein, The ground environment data comprises polarization data of the region to be projected; the performing of the ground environment analysis on the ground environment data to obtain an environment analysis result further comprises: processing the polarization data of the region to be projected through a convolutional neural network to obtain the ground texture.

5. The adaptive projection method of claim 1 or 2, wherein, The ground environment data comprises electromagnetic wave time domain data; the performing of the ground environment analysis on the ground environment data to obtain an environment analysis result further comprises: converting the electromagnetic wave time domain data into frequency domain data through fast Fourier transform; determining the ground roughness corresponding to the frequency domain data according to a preset roughness frequency domain mapping relationship.

6. The adaptive projection method of claim 1 or 2, wherein, The ground environment data further comprises temperature data and reflectivity data; the performing of the ground environment analysis on the ground environment data to obtain an environment analysis result further comprises: determining the ground material corresponding to the temperature data and the reflectivity data according to a preset mapping relationship among temperature, reflectivity, and material.

7. The adaptive projection method of claim 1 or 2, wherein, The adjusting of the projection strategy according to the environment analysis result comprises: performing high-low drop compensation according to the ground flatness, adjusting projection light intensity according to the ground texture and / or the ground roughness, adjusting a projection angle according to the ground roughness, and adjusting a projection light source color according to the ground material.

8. An adaptive projection device, characterized by, The method comprises: a data acquisition module configured to acquire ground environment data of a region to be projected; an environment analysis module configured to perform ground environment analysis on the ground environment data to obtain an environment analysis result, wherein the environment analysis result comprises at least one of ground flatness, ground texture, ground roughness, and ground material; a strategy adjustment module configured to adjust a projection strategy according to the environment analysis result.

9. An electronic device, comprising: comprise a memory and a processor; the memory is configured to store a computer program; the processor is configured to implement the adaptive projection method of any one of claims 1-7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The storage medium has a computer program stored thereon, and the adaptive projection method of any one of claims 1-7 is implemented when the computer program is executed by a processor.

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