Distributed Object Detection With Linear SVMs

doi:10.1109/TCYB.2014.2301453

OPT OpenIR > 光谱成像技术研究室

	Distributed Object Detection With Linear SVMs
	Pang, Yanwei 1; Zhang, Kun 1; Yuan, Yuan2 ; Wang, Kongqiao 3
作者部门	光学影像学习与分析中心
	2014-11-01
发表期刊	IEEE TRANSACTIONS ON CYBERNETICS
ISSN	2168-2267
卷号	44 期号:11 页码:2122-2133
摘要	In vision and learning, low computational complexity and high generalization are two important goals for video object detection. Low computational complexity here means not only fast speed but also less energy consumption. The sliding window object detection method with linear support vector machines (SVMs) is a general object detection framework. The computational cost is herein mainly paid in complex feature extraction and innerproduct-based classification. This paper first develops a distributed object detection framework (DOD) by making the best use of spatial-temporal correlation, where the process of feature extraction and classification is distributed in the current frame and several previous frames. In each framework, only subfeature vectors are extracted and the response of partial linear classifier (i.e., subdecision value) is computed. To reduce the dimension of traditional block-based histograms of oriented gradients (BHOG) feature vector, this paper proposes a cell-based HOG (CHOG) algorithm, where the features in one cell are not shared with overlapping blocks. Using CHOG as feature descriptor, we develop CHOG-DOD as an instance of DOD framework. Experimental results on detection of hand, face, and pedestrian in video show the superiority of the proposed method.
文章类型	Article
关键词	Cell-based Histograms Of Oriented Gradients (Chog) Computer Vision Feature Extraction Linear Classifier Machine Learning Object Detection
WOS标题词	Science & Technology ; Technology
DOI	10.1109/TCYB.2014.2301453
收录类别	SCI ; EI
关键词[WOS]	SUPPORT VECTOR MACHINES ; FACE-RECOGNITION ; NEUROMUSCULAR DISORDERS ; TRACKING ; FEATURES ; LOCALIZATION ; DIAGNOSIS ; SYSTEM
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS记录号	WOS:000343319700012
引用统计	被引频次：58[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.opt.ac.cn/handle/181661/22371
专题	光谱成像技术研究室
作者单位	1.Tianjin Univ, Sch Elect Informat Engn, Tianjin 300072, Peoples R China 2.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr Opt Imagery Anal & Learning, State Key Lab Transient Opt & Photon, Xian 710119, Peoples R China 3.Nokia Res Ctr, Beijing 100176, Peoples R China
推荐引用方式 GB/T 7714	Pang, Yanwei,Zhang, Kun,Yuan, Yuan,et al. Distributed Object Detection With Linear SVMs[J]. IEEE TRANSACTIONS ON CYBERNETICS,2014,44(11):2122-2133.
APA	Pang, Yanwei,Zhang, Kun,Yuan, Yuan,&Wang, Kongqiao.(2014).Distributed Object Detection With Linear SVMs.IEEE TRANSACTIONS ON CYBERNETICS,44(11),2122-2133.
MLA	Pang, Yanwei,et al."Distributed Object Detection With Linear SVMs".IEEE TRANSACTIONS ON CYBERNETICS 44.11(2014):2122-2133.

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