摘要:
Disclosed is an object detection method used to detect an object in an image pair corresponding to a current frame. The image pair includes an original image of the current frame and a disparity map of the same current frame. The original image of the current frame includes at least one of a grayscale image and a color image of the current frame. The object detection method comprises steps of obtaining a first detection object detected in the disparity map of the current frame; acquiring an original detection object detected in the original image of the current frame; correcting, based on the original detection object, the first detection object so as to obtain a second detection object; and outputting the second detection object.
摘要:
A method and a device are disclosed for detecting a drivable region of a road, the method comprising the steps of: deriving a disparity map from a gray-scale map including the road and detecting the road from the disparity map; removing a part with a height above the road greater than a predetermined height threshold from the disparity map so as to generate a sub-disparity map; converting the sub-disparity map into a U-disparity map; detecting the drivable region from the U-disparity map; and converting the drivable region detected from the U-disparity map into the drivable region within the gray-scale map.
摘要:
Disclosed is an object tracking method. The method includes steps of obtaining a first boundary region of a waiting-for-recognition object in the disparity map related to the current frame; calculating a probability of each valid pixel in the first boundary region so as to get a pixel probability map of the waiting-for-recognition object; obtaining historic tracking data of each tracked object, which includes identifier information of the tracked object and a pixel probability map related to each of one or more prior frame related disparity maps prior to the disparity map related to the current frame; determining identifier information of the waiting-for-recognition object, and updating the pixel probability map of the waiting-for-recognition object; and updating, based on the updated pixel probability map of the waiting-for-recognition object, the first boundary region of the waiting-for-recognition object, so as to get a second boundary region of the waiting-for-recognition object.
摘要:
A method and a system for analyzing a target in a stereo image by displaying the stereo image using a cascade structure are disclosed. The method includes for the input stereo image, generating, based on a first relevant feature, rule or model of the stereo image, at least a first first-level structure map, each of the first first-level structure maps being generated based on an individual tolerance level of the first relevant feature, rule or model, and each of the first first-level structure maps including the target at an individual first division level; and at least partly integrating the first first-level structure maps and analyzing the target in the stereo image, to obtain a structure map of a first-level target analysis result including the target.
摘要:
A method and an apparatus are disclosed for detecting a continuous road partition with a height, the method comprising the steps of: obtaining disparity maps having the continuous road partition, and U-disparity maps corresponding to the disparity maps; obtaining an intermediate detection result of the continuous road partition detected from the U-disparity maps of first N frames; and detecting the continuous road partition from the U-disparity map of a current frame, based on the obtained intermediate detection result.
摘要:
Disclosed are a method and a system for detecting a vehicle position by employing a polarization image. The method comprises a step of capturing a polarization image by using a polarization camera; a step of acquiring two road shoulders in the polarization image based on a difference between a road surface and each of the two road shoulders in the polarization image, and determining a part between the two road shoulders as the road surface; a step of detecting at least one vehicle bottom from the road surface based on a significant pixel value difference between each wheel and the road surface in the polarization image; and a step of generating a vehicle position from the vehicle bottom based on a pixel value difference between a vehicle outline corresponding to the vehicle bottom and background in the polarization image.