Harman International (china) Holdings Co., Ltd.

Zhang Yankun

Norman Weyrich

Hong Chuyang

A computer-implemented method for determining an egomotion parameter using an egomotion estimation system is provided. First and second image frames are obtained. A first portion of the first image frame and a second portion of the second image frame are selected to respectively obtain a first sub-image and a second sub-image. A transformation is performed on each of the first sub-image and the second sub-image to respectively obtain a first perspective image and a second perspective image. The second perspective image is iteratively adjusted to obtain multiple adjusted perspective images. Multiple difference values are determined that respectively correspond to the respective difference between the first perspective image and the adjusted perspective images. A translation vector for an ego motion parameter is determined. The translation vector corresponds to one of the multiple difference values.

Egomotion estimation system and method

Systems and methods for detecting obstacles using a single camera positioned on an apparatus in motion over an area of motion, or stationary over a moving area of motion. In an example method, a video stream of images is captured of the area of motion. The images in the video stream may be corrected for lens distortion prior to further processing. An Nth image frame is selected from a sequence of N images in the video stream. A set of N&#x2212;1 difference images is calculated by subtracting each of the N&#x2212;1 previous images from the Nth image. The N&#x2212;1 difference images are added to one another to generate a combined difference image. A perspective transformation is performed on the combined difference image to generate a transformed image. The transformed image is analyzed to detect edges of obstacles in the transformed image. A signal indicating detection of an obstacle in the area of motion may then be generated.

Fast obstacle detection

A computer-implemented method of detecting objects in a path of a vehicle is provided. An image frame that depicts the path of the vehicle is obtained. An edge-image corresponding to the image frame is generated. A binary image corresponding to the edge-image is also generated. One or more blobs in the binary image that respectively correspond to one or more objects in the image frame are identified. Based on an analysis of the blobs in the binary image, a determination is made that one of the objects in the image frame is an obstacle in the path of the vehicle.

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Shanghai, China

Zhang Yankun