基于图像序列的运动目标检测识别的关键技术研究

doi:10.3969/j.issn.1000-1158.2020.12.05

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Abstract To improve the recognition of moving target detection, the pros and cons of various moving target detection algorithms were analyzed, the global adaptive frame difference method and the codebook model based background subtraction method was proposed to detect moving targets simultaneously for the same target.The method used the masks of moving target and then analyzed them by rectangles, so that the pictures in the rectangle can be extracted out.Next, adjust the rectangle and extract the HOG features of the image, classify through trained SVM.In the training process, the bootstrap method is applied to optimize the trainer for difficult situations.Experiments show that compared with the traditional HOG+SVM multiscale detection algorithm, this method can increase the speed and accuracy by about 20%, and it can be used as a reference method for moving target detection and recognition.

Key words： metrology moving target detection frame difference method codebook HOG feature SVM

Received: 15 April 2019 Published: 08 December 2020

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TB96

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	Articles by authors
	XUE Zhen
	YU Lian-zhi
	HU Chan-juan

Cite this article:

XUE Zhen,YU Lian-zhi,HU Chan-juan. Research on Key Techniques of Moving Target Detection and Recognition Based on Image Sequence[J]. Acta Metrologica Sinica, 2020, 41(12): 1475-1481.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2020.12.05 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2020/V41/I12/1475

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