Multi-pose Pedestrian Detection Based on Posterior Multiple Sparse Dictionaries

Authors

Lingkang Gu, College of Computer and Information, Anhui Polytechnic University, Wuhu 241000, China;
Mingzheng Zhou, College of Computer and Information, Anhui Polytechnic University, Wuhu 241000, China;
Wang Jun, College of Computer and Information, Anhui Polytechnic University, Wuhu 241000, China;
Xiu Yu, College of Computer and Information, Anhui Polytechnic University, Wuhu 241000, China;

Abstract

Abstract: In order to detect pedestrians effectively, a multi-pose pedestrian detection method based on posterior multiple sparse dictionaries was proposed. Through pre-learning multiple different sparse dictionaries, and sparse coding the image, statistics for each dictionary corresponds to sparse coding histogram as the pedestrian image feature descriptor. The common information of multiple sparse dictionary features of all positive samples was obtained, and the feature of a single pedestrian sample was weighted, and the features of a posteriori multiple sparse dictionary could be obtained. Then pedestrians of different poses and views were divided into subclasses with clustering algorithm. A classifier was trained for each subclass. A multi-pose-view ensemble classifier was trained to combine the output values of different subclass classifiers with an equally weighted sum rule. Experimental results on different datasets suggest that the proposed posterior feature is more than the classical sparse dictionary and other typical features. Compared with the existing methods, by combining the posterior feature and the multi-pose-view ensemble classifier, the proposed method improves the detection accuracy effectively.

Recommended Citation

Gu, Lingkang; Zhou, Mingzheng; Jun, Wang; and Yu, Xiu (2020) "Multi-pose Pedestrian Detection Based on Posterior Multiple Sparse Dictionaries," Journal of System Simulation: Vol. 29: Iss. 2, Article 12.
DOI: 10.16182/j.issn1004731x.joss.201702012
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss2/12

First Page

326

Revised Date

2016-07-14

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201702012

Last Page

331

CLC

TP391.4

Recommended Citation

Gu Lingkang, Zhou Mingzheng, Wang Jun, Xiu Yu. Multi-pose Pedestrian Detection Based on Posterior Multiple Sparse Dictionaries[J]. Journal of System Simulation, 2017, 29(2): 326-331.

DOI

10.16182/j.issn1004731x.joss.201702012