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The 360 degree panoramic view algorithm refers to the process of capturing multiple images and stitching them together to generate a complete 360 degree panoramic image. This algorithm typically involves a series of techniques such as image stitching, image registration, geometric correction, and color balance. In terms of implementation, computer vision and image processing techniques are usually used, such as using image processing libraries such as OpenCV for image processing and stitching.
Automatic brightness equalization refers to automatically adjusting the brightness of different regions or channels when processing an image or video, making the brightness distribution of the entire image or video more uniform, while avoiding situations of over brightness or over darkness. This technology typically involves a series of operations such as color space conversion and brightness space adjustment for images or videos. In terms of implementation, it can be achieved by calculating the brightness distribution of images or videos and automatically adjusting the brightness of different regions.
One click automatic calibration refers to the automatic completion of camera or sensor calibration through one click operation when using the camera or sensor. This technology usually involves calibrating the internal and external parameters of the camera or sensor to ensure that the camera or sensor can accurately capture the target object. In terms of implementation, computer vision techniques are usually used, such as using visual libraries such as OpenCV for camera or sensor calibration.
Adaptive 3D models refer to the ability to automatically generate 3D models that adapt to different scenes based on actual situations. This technology typically involves a series of operations such as modeling 3D models, texture mapping, and lighting processing. In terms of implementation, 3D models can be generated by scanning the scene and using 3D reconstruction algorithms, or by using intelligent algorithms to automatically recognize objects in the scene and generate corresponding 3D models.
Blind spot pedestrian detection and distance measurement refer to detecting pedestrians in the blind spot and measuring their distance from the vehicle when using the vehicle, in order to avoid collision accidents. This technology typically involves the processing and analysis of images or videos, such as using computer vision technology to detect human features in images or videos and calculate distances. In terms of implementation, blind spot pedestrian detection and distance measurement can be achieved by using sensors such as radar, LiDAR, and ultrasound.
Supporting multi-channel splicing (3/4/6 channels) refers to merging multiple image or video channels into a complete image or video output. This technology typically involves the processing and stitching of multiple images or video channels, such as using image stitching algorithms to merge multiple image channels into a complete panoramic image, or using video stitching algorithms to merge multiple video channels into a complete panoramic video. In terms of implementation, multi-channel splicing can be achieved through the use of computer vision and image processing techniques.
The 360 degree panoramic view algorithm refers to the process of capturing multiple images and stitching them together to generate a complete 360 degree panoramic image. This algorithm typically involves a series of techniques such as image stitching, image registration, geometric correction, and color balance. In terms of implementation, computer vision and image processing techniques are usually used, such as using image processing libraries such as OpenCV for image processing and stitching.
Automatic brightness equalization refers to automatically adjusting the brightness of different regions or channels when processing an image or video, making the brightness distribution of the entire image or video more uniform, while avoiding situations of over brightness or over darkness. This technology typically involves a series of operations such as color space conversion and brightness space adjustment for images or videos. In terms of implementation, it can be achieved by calculating the brightness distribution of images or videos and automatically adjusting the brightness of different regions.
One click automatic calibration refers to the automatic completion of camera or sensor calibration through one click operation when using the camera or sensor. This technology usually involves calibrating the internal and external parameters of the camera or sensor to ensure that the camera or sensor can accurately capture the target object. In terms of implementation, computer vision techniques are usually used, such as using visual libraries such as OpenCV for camera or sensor calibration.
Adaptive 3D models refer to the ability to automatically generate 3D models that adapt to different scenes based on actual situations. This technology typically involves a series of operations such as modeling 3D models, texture mapping, and lighting processing. In terms of implementation, 3D models can be generated by scanning the scene and using 3D reconstruction algorithms, or by using intelligent algorithms to automatically recognize objects in the scene and generate corresponding 3D models.
Blind spot pedestrian detection and distance measurement refer to detecting pedestrians in the blind spot and measuring their distance from the vehicle when using the vehicle, in order to avoid collision accidents. This technology typically involves the processing and analysis of images or videos, such as using computer vision technology to detect human features in images or videos and calculate distances. In terms of implementation, blind spot pedestrian detection and distance measurement can be achieved by using sensors such as radar, LiDAR, and ultrasound.
Supporting multi-channel splicing (3/4/6 channels) refers to merging multiple image or video channels into a complete image or video output. This technology typically involves the processing and stitching of multiple images or video channels, such as using image stitching algorithms to merge multiple image channels into a complete panoramic image, or using video stitching algorithms to merge multiple video channels into a complete panoramic video. In terms of implementation, multi-channel splicing can be achieved through the use of computer vision and image processing techniques.
