Parallel high definition video vehicle detection method based on GPU

A technology of vehicle detection and high-definition video, which is applied in closed-circuit television systems, instruments, character and pattern recognition, etc. It can solve the problems of not being able to give the position information of the target, and the calculation speed is difficult to meet real-time performance, and achieve reliable performance and adaptability wide effect

Active Publication Date: 2012-09-26
ZTE ITS CO LTD
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AI Technical Summary

Problems solved by technology

[0005] The calculation speed of the algorithm mentioned above has been significantly improved compared with the nonlinear SVM (support vector machine). For high-definition video surveillance, its calculation speed is still difficult to meet the real-time requirements, and it can only judge whether the target object appears in the video. , the location information of the target cannot be given

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  • Parallel high definition video vehicle detection method based on GPU
  • Parallel high definition video vehicle detection method based on GPU
  • Parallel high definition video vehicle detection method based on GPU

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Embodiment

[0063] The industrial computer on the roadside of intersection A reads the original video data captured by the high-definition surveillance camera at the intersection in real time; the CPU in the industrial computer controls the video data to be directly copied from the camera to the video memory of the graphics card through the internal memory. The GPU quickly decodes the original video data on the video memory of the graphics card in parallel, and converts it into a frame of grayscale image. After the GPU converts the video data stream into a frame of grayscale images, the GPU calculates in real time whether there is a car in each frame of the image; specifically:

[0064] 1), consider a frame of grayscale image as 8×8 image sub-block images, the following calculations require threads in the same thread block to perform parallel calculations on the same image sub-block;

[0065] 2), extract the SIFT features of each image sub-block in parallel, and obtain the feature matrix ...

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Abstract

The invention relates to a parallel high definition video vehicle detection method based on GPU. The method comprises the following steps: a, an original video stream output by a high definition monitoring camera is transmitted into a display memory of a display card, and GPU in the display card carries out parallel decoding on the original video stream to get a frame gray image; b, GPU divides each frame gray image into N*N image blocks, and carries out parallel extraction on SIFT characteristics of each image block; c, GPU carries out parallel sparse coding on each image block; d, a constraint matrix U corresponding to each image block is acquired by parallel calculation; e, a characteristic vector zk of each image block is parallelly calculated; f, GPU carries out parallel linear classification and identification on the above characteristic vector zk obtained by calculation to obtaina corresponding judgment result fk; and g, GPU returns the judgment result fk into CPU, and CPU controls the working state of the high definition monitoring camera according to the judgment result fk. The method provided by the invention can meet the requirement of real-time monitoring of the high definition video, and has the advantages of wide suitability, safety and reliability.

Description

technical field [0001] The invention relates to a vehicle detection method, in particular to a GPU (Graphic Processing Unit)-based parallel high-definition video vehicle detection method, belonging to the technical field of high-definition video vehicle detection. Background technique [0002] With the development of technology, in modern intelligent transportation systems, the vehicle detection and recognition method based on surveillance video has become the mainstream means and development trend of vehicle detection in intelligent transportation systems. How to complete high-accuracy vehicle detection in real time is a hot and difficult point in current research. [0003] At present, in the field of pattern recognition, the relatively mature technology is SVM to complete classification detection and various improved algorithms. Among them, we found that the algorithm based on sparse coding and linear SVM classifier has achieved very good results. [0004] The algorithm ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N7/18G06K9/00
Inventor 李健郑志彤彭敏刘海峰李翔黄溅华
Owner ZTE ITS CO LTD
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