Moving object detecting method based on graphics processing unit (GPU)

A moving target and detection method technology, applied in the field of GPU-based moving target detection, can solve problems such as accuracy and real-time performance

Inactive Publication Date: 2013-04-03
HUAZHONG UNIV OF SCI & TECH
View PDF2 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] For the defects of the prior art, the object of the present invention is to provide a GPU-based moving object detection method, aiming to solve the accuracy and real-time p

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Moving object detecting method based on graphics processing unit (GPU)
  • Moving object detecting method based on graphics processing unit (GPU)
  • Moving object detecting method based on graphics processing unit (GPU)

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0084] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0085] like figure 1 As shown, the present invention's GPU-based moving target detection method comprises the following steps:

[0086] (1) Load video training data into GPU memory;

[0087] (2) Store video training data in the form of local Z-shaped blocks;

[0088] (3) Extract multi-feature data of video training data, and use adaptive weight model to fuse multi-feature data to establish a codebook model based on multi-feature; multi-feature data includes intensity, color, texture, etc.;

[0089] (4) Load the video test data into the GPU memory;

[0090] (5) Store video test data in the form ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a moving object detecting method based on a graphics processing unit (GPU). The moving object detecting method comprises the steps of loading video training data to a GPU video memory, memorizing the video training data in a local Z-shaped block mode, extracting multi-feature data of the video training data, adopting a self-adaption weight model to integrate the multi-feature data so as to build a codebook model based on multiple features, loading video testing data to the GPU video memory, memorizing the video testing data in a local Z-shaped block mode, utilizing the codebook model based on multiple features to perform moving object detection to the video testing data, utilizing a moving object detection result to update the codebook model based on multiple features and memorizing the moving object detection result on the GPU side. The moving object detecting method has the advantages of being high in applicability, strong in expandability, high in efficiency and low in cost and enables moving object detection to meet the requirements for accuracy and timeliness.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition and GPU-based general computing, and more specifically relates to a GPU-based moving target detection method. . Background technique [0002] With the improvement of people's safety awareness and the rapid development of security technology and industry, video surveillance systems are widely used in people's lives. The traditional video surveillance system requires video surveillance personnel to monitor the video continuously for a long time, analyze the abnormal situation in the video, record and store the abnormal information, and make corresponding decisions to deal with the abnormal situation. This manual-based monitoring method, when the video surveillance personnel are tired and negligent, will lead to a large number of false positives and false positives, which has great potential safety hazards. Surveillance video has increased geometrically, and it is impossible to monitor ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06T7/20G06T1/20
Inventor 金海郑然邓巍章勤
Owner HUAZHONG UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products