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 method and a system for traffic light detection are provided. The method may include: obtaining a color image; calculating pixel response values for pixels of the color image, respectively, where each of the pixel response values may be calculated using R, G, and B values of a corresponding pixel directly, such that pixel response values of red traffic light pixels are substantially distributed on a first side of a predetermined range and pixel response values of green traffic light pixels are substantially distributed on a second side of the predetermined range which is opposite to the first side; identifying pixels whose pixel response values are distributed on the first side or the second side as candidate pixels; identifying candidate blobs based on the candidate pixels; and verifying whether the candidate blobs are traffic lights. Efficiency and reliability may be improved.

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 surround view monitoring system configured to synthesize a birds-eye-view image of an area around a vehicle includes a camera and a controller. The camera is configured to capture a present-image of a field-of-view about the vehicle and output a signal indicative of the present-image. The present-image includes a feature of the vehicle. The controller is configured to receive the signal, compare the present-image to a reference-image from an initial calibration of the system. The reference-image also includes the feature. The controller is further configured to determine a correction table for the present-image to align the feature in the present-image to the feature in the reference-image.

Abstract: A method and a system for traffic light detection are provided. The method may include: obtaining a color image; calculating pixel response values for pixels of the color image, respectively, where each of the pixel response values may be calculated using R, G, and B values of a corresponding pixel directly, such that pixel response values of red traffic light pixels are substantially distributed on a first side of a predetermined range and pixel response values of green traffic light pixels are substantially distributed on a second side of the predetermined range which is opposite to the first side; identifying pixels whose pixel response values are distributed on the first side or the second side as candidate pixels; identifying candidate blobs based on the candidate pixels; and verifying whether the candidate blobs are traffic lights. Efficiency and reliability may be improved.

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: Disclosed are a flexible polymer, particles made from same, and a process for preparing the particles. This flexible polymer is obtained from copolymerizing monomer (A) and monomer (B), wherein monomer (A) is one or more water-insoluble unsaturated diene monomers; monomer (B) is at least one compound with the general formula of wherein R is C1-C12alkyl, C1-C12 alkyl aryl, C1-C12 alkyl ether or C1-C12alkyl ester. Monomer (A) is in an amount of 60-90% by weight of the total combined weight of monomer (A) and monomer (B). Monomer (B) is in an amount of 10-40% by weight of the total combined weight of monomer (A) and monomer (B). The flexible polymer particles show excellent flexibility, deformability, elasticity as well as stability. They can be used in oilfields in nearby wellbore profile control and in-depth profile control or as in-depth flooding fluid diverting agents.

Abstract: Disclosed are a flexible polymer, particles made from same, and a process for preparing the particles. This flexible polymer is obtained from copolymerizing monomer (A) and monomer (B), wherein monomer (A) is one or more water-insoluble unsaturated diene monomers; monomer (B) is at least one compound with the general formula of wherein R is C1-C12alkyl, C1-C12 alkyl aryl, C1-C12 alkyl ether or C1-C12alkyl ester. Monomer (A) is in an amount of 60-90% by weight of the total combined weight of monomer (A) and monomer (B). Monomer (B) is in an amount of 10-40% by weight of the total combined weight of monomer (A) and monomer (B). The flexible polymer particles show excellent flexibility, deformability, elasticity as well as stability. They can be used in oilfields in nearby wellbore profile control and in-depth profile control or as in-depth flooding fluid diverting agents.