Gan Pengkun,Tao Ling,and Long Wei.Cascade pedestrian detection based on the deformable part models and histograms of sparse codes features[J].Journal of Shenzhen University Science and Engineering,2015,32(6):563-570.[doi:10.3724/SP.J.1249.2015.06563]





Cascade pedestrian detection based on the deformable part models and histograms of sparse codes features
南昌大学信息工程学院,南昌 330000
Gan Pengkun Tao Ling and Long Wei
School of Information Engineering, Nanchang University, Nanchang 330031, P.R.China
图像处理 人体检测 稀疏特征 部件模型 弱标签隐藏变量支持向量机学习算法 级联检测
image processing human detection sparse feature part model weak label hidden variable support vector machine learning algorithm cascade detection
N 34
We propose a new sparse encoding based deformable part modelling method to overcome the defect of histogram of orientation gradients algorithm that can not detect fuzzy boundary and smooth feature region inside an object. By using sparse learning, we obtain the image feature operator based on histograms of sparse codes. We use weak label latent variable structured support vector machine to train the feature to derive part model, which is then combined with cascade algorithm to detect human body targets. Experimental results show that the detection time of hybrid model based on cascade method is about a quater that of the hybrid model alone and semantic model. The proposed method has better robustness and recognition ability.


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Foundation:National Natural Science Foundation of China(61261011)
Corresponding author:Professor Tao Ling. E-mail: tt123@139.com
Citation:Gan Pengkun,Tao Ling,Long Wei. Cascade pedestrian detection based on the deformable part models and histograms of sparse codes features[J]. Journal of Shenzhen University Science and Engineering, 2015, 32(6): 563-570.(in Chinese)
引文:甘鹏坤,陶凌,龙伟.基于可变形部件模型及稀疏特征的行人检测[J]. 深圳大学学报理工版,2015,32(6):563-570.
更新日期/Last Update: 2015-11-06