CASIA OpenIR  > 智能制造技术与系统研究中心  > 先进制造与自动化
Pedestrian Detection Using Boosted HOG Features
Zhen-rui Wang; Yulan Jia; Hua Huang; Shuming Tang
2008
Conference NameThe Proceedings of the 11th IEEE International Conference on Intelligent Transportation Systems
Source PublicationIEEE INTELLIGENT SYSTEMS
Conference DateOctober 12-15, 2008
Conference PlaceBeijing, China
AbstractThis paper presents a novel approach in pedestrian detection in static images. The state-of-art feature named Histograms of Oriented Gradients (HOG) [1] is adopted as the basic feature which we modify and create a new feature using boosting algorithm. The detection is achieved by training a linear SVM with the boosted HOG feature. We experimentally demonstrate that our solution achieve comparable performance as the HOG algorithm on the INRIA pedestrian dataset yet considerably reduce storage requirement and simplify the computation in terms of elementary operations.
KeywordSupport Vector Machines Intelligent Transportation Systems Support Vector Machine Classification Automation Humans Computer Vision Histograms Shape Infrared Detectors Computational Efficiency
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12394
Collection智能制造技术与系统研究中心_先进制造与自动化
Corresponding AuthorZhen-rui Wang
Recommended Citation
GB/T 7714
Zhen-rui Wang,Yulan Jia,Hua Huang,et al. Pedestrian Detection Using Boosted HOG Features[C],2008.
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