Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A method and a system for image layer composition are provided. The method may include detecting whether a plurality of computing devices of a computing system have available resource for performing image layer composition. The method also includes receiving a plurality of image layers and controlling at least one computing device detected having available resource for performing image layer composition to compose the plurality of image layers. Composition efficiency may be improved.

Abstract: 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.

Abstract: 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.

Abstract: The present application provides pedestrian detection system and method. A pedestrian detection method includes: obtaining an image captured by a camera; identifying a pedestrian candidate in the image; 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 pedestrian candidate is a true positive by determining whether the actual height of the pedestrian candidate is within a predetermined pedestrian height range. The system and method of the present application have lower cost and higher accuracy compared with conventional technologies.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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?1 difference images is calculated by subtracting each of the N?1 previous images from the Nth image. The N?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.

Abstract: 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.

Abstract: System and method for adjusting the parameters of an image capturing device, such as a camera that captures a sequence of images and generates another image from the captured sequence of images using parameters that identify a virtual location and overlaying the generated image with a 3D generated image where distortion compensation has occurred been applied to the image.

Abstract: A multiple-view virtual camera system comprising one or more image source units, an image processing unit, a parameter setting unit in signal communication with the image processing unit, and a display in signal communication with the image processing unit. The display is configured to display images generated by the image processing unit to a user of the virtual camera system, where the displayed images are configured according to image-related parameters input by a user of the multiple-view camera system through the parameter setting unit. The parameter setting unit may include a user interface, such as a single-touch or multi-touch touchscreen display, configured to accept input from the user that adjusts the parameters that are transmitted to the image processing unit and utilized by the image processing unit. A method of interactively controlling the virtual camera system by a user of a motor vehicle is also disclosed.

Abstract: 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.

Abstract: 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?1 difference images is calculated by subtracting each of the N?1 previous images from the Nth image. The N?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.

Abstract: 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.