Pedestrian detection in unseen scenes by dynamically updating visual words

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 光学影像学习与分析中心

	Pedestrian detection in unseen scenes by dynamically updating visual words
	Cao, Xianbin 1; Wang, Li 1; Ning, Bo 2; Yuan, Yuan3 ; Yan, Pingkun 3
刊名	neurocomputing
	2013-11-07
卷号	119 页码:232-242
关键词	Pedestrian detection Adaptive detector Bag of visual words Manifold leaning
英文摘要	adapting trained detectors to unseen scenes is a critical problem in pedestrian detection. the performance of trained detector may drop quickly when scenes vary significantly. retraining a detector with labeled samples from the new scenes may improve its performance. however, it is difficult to obtain enough labeled samples in real applications. in this paper, a novel bag of visual words based method is proposed to detect pedestrians in unseen scenes by dynamically updating the key words. the proposed method achieves its adaptability by using three strategies covering key word selection, detector invariance, and codebook update: (1) in order to select typical words representing pedestrians, a low dimensional model of visual words is built to describe their distribution and select key words using manifold learning. (2) matching confidence vector (mcv), a novel visual words measurement is proposed, which aims to generate a uniform input vector for the fixed detector applied to different pedestrian codebooks. (3) when detecting pedestrians under changing road conditions, the key word set will be dynamically adjusted according to the matching frequency of each word to adapt the detector to the new scenes. by employing the above strategies, the proposed method is able to detect pedestrians in different scenes without retraining the detector. experiments in different scenes showed that our proposed method can achieve better adaptability to various scenes and get better performance than other existing methods in unseen scenes. (c) 2013 elsevier b.v. all rights reserved.
WOS标题词	science & technology ; technology
类目[WOS]	computer science, artificial intelligence
研究领域[WOS]	computer science
关键词[WOS]	nonlinear dimensionality reduction ; object detection ; features
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000323851800029
公开日期	2015-06-30
内容类型	期刊论文
源URL	[http://ir.opt.ac.cn/handle/181661/23470]
专题	西安光学精密机械研究所_光学影像学习与分析中心
作者单位	1.Beihang Univ, Beijing 100191, Peoples R China 2.Univ Sci & Technol China, Hefei 230026, Peoples R China 3.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr Opt Imagery Anal & Learning OPTIMAL, Xian 710119, Shaanxi, Peoples R China
推荐引用方式 GB/T 7714	Cao, Xianbin,Wang, Li,Ning, Bo,et al. Pedestrian detection in unseen scenes by dynamically updating visual words[J]. neurocomputing,2013,119:232-242.
APA	Cao, Xianbin,Wang, Li,Ning, Bo,Yuan, Yuan,&Yan, Pingkun.(2013).Pedestrian detection in unseen scenes by dynamically updating visual words.neurocomputing,119,232-242.
MLA	Cao, Xianbin,et al."Pedestrian detection in unseen scenes by dynamically updating visual words".neurocomputing 119(2013):232-242.