Harman International Industries, Inc.

Harman International (china) Holdings Co., Ltd.

Harman Becker Automotive Systems Gmbh

Norman Weyrich

Yankun Zhang

Chuyang Hong

Yun Zhou

Ruyi Jiang

Stephan Bergmann

Hong Chuyang

Zhang Yankun

Jia He

A method and system for generating a surround view are provided. The method may include: establishing a surround surface; obtaining a plurality of images of surroundings; and projecting the images onto the surround surface based on a projection relationship between points on the surround surface and pixels on the images to generate a surround view, where the projection relationship may change with heights of the points on the surround surface. An improved projection effect may be obtained.

Method and system for generating a surround view

The present application provides pedestrian detection system and method. A pedestrian detection method includes obtaining an image captured by a camera, and identifying a pedestrian candidate in the image. According to the method, the pedestrian candidate is confirmed by transforming the image into a top view image, calculating the actual height of the pedestrian candidate based on the top view image and extrinsic parameters of the camera, and determining whether the actual height of the pedestrian candidate is within a predetermined pedestrian height range.

System and method for detecting pedestrians using a single normal camera

A moving objects detection method is disclosed. The method may include: identifying a plurality of feature points based on a plurality of video frames; selecting from the plurality of feature points to form a first and a second groups of feature points based on correlations between the plurality of feature points; and identifying in at least one video frame two segments based on the first and the second groups of feature points, respectively, as detected moving objects, where a correlation between two feature points may include a distance component and a movement difference component, where the distance component is related to a distance between the two feature points, and the movement difference component is related to a difference between corresponding movements of the two feature points. A moving objects detection system is also provided.

Method and system for detecting moving objects

A method for detecting traffic lights is provided. The method includes: obtaining a color image captured by a camera; converting the color image into a first monochrome scale image; converting the first monochrome scale image into a first binary image; identifying a first set of candidate blobs in the first binary image based on at least one predetermined geometric parameter; and determine whether a first region in the color image, which first region corresponds to one of the first set of candidate blobs, is a green traffic light using a green traffic light classifier. The accuracy and efficiency may be improved.

Method and system for detecting traffic lights

The present application provides an obstacle detection system and method thereof. The obstacle detection method comprises: obtaining a first image captured by a camera at a first time point; identifying a vertical edge candidate in the first image, and measuring a first length of the vertical edge candidate based on the first image; obtaining a second image captured by the camera at a second time point; measuring a second length of the vertical edge candidate based on the second image; calculating a difference between the first length and the second length; and comparing the difference with a predetermined length difference threshold, if the difference is greater than the length difference threshold, outputting a message that an obstacle is found.

System and method for detecting obstacles using a single camera

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

Norman Weyrich