[1]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.[doi:10.3724/SP.J.1249.2015.06563]
 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]
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基于可变形部件模型及稀疏特征的行人检测()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第32卷
期数:
2015年第6期
页码:
563-570
栏目:
电子与信息科学
出版日期:
2015-11-23

文章信息/Info

Title:
Cascade pedestrian detection based on the deformable part models and histograms of sparse codes features
文章编号:
201506002
作者:
甘鹏坤陶凌龙伟
南昌大学信息工程学院,南昌 330000
Author(s):
Gan Pengkun Tao Ling and Long Wei
School of Information Engineering, Nanchang University, Nanchang 330031, P.R.China
关键词:
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
Keywords:
image processing human detection sparse feature part model weak label hidden variable support vector machine learning algorithm cascade detection
分类号:
N 34
DOI:
10.3724/SP.J.1249.2015.06563
文献标志码:
A
摘要:
针对方向梯度直方图算法无法处理模糊边界且忽略了物体内平滑的特征区域的问题,提出一种基于稀疏编码的可变形部件模型算法.通过稀疏学习得到稀疏编码直方图特征算子的图像特征,利用弱标签隐藏变量结构化支持向量机学习算法对特征进行训练得到部件模型,再结合级联检测算法对人体目标进行识别检测.实验结果显示,混合模型结合级联方法的检测耗时约是混合模型和语义模型平均检测耗时的1/4,与目前其他已有算法比较,所提方法更加鲁棒和具有识别力.
Abstract:
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.

参考文献/References:

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备注/Memo

备注/Memo:
Received:2015-09-07;Accepted:2015-10-28
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)
基金项目:国家自然科学基金资助项目(61261011)
作者简介:甘鹏坤(1991—),男(汉族),河南省信阳市人,南昌大学硕士研究生.E-mail:1158169508@qq.com
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