Multiple deep features learning for object retrieval in surveillance videos

doi:10.1049/iet-cvi.2015.0291

	Multiple deep features learning for object retrieval in surveillance videos
	Guo, Haiyun; Wang, Jinqiao; Lu, Hanqing
发表期刊	IET COMPUTER VISION
	2016-02-26
卷号	10 期号:4 页码:268-271
文章类型	Article
摘要	Efficient indexing and retrieving objects of interest from large-scale surveillance videos are a significant and challenging topic. In this study, the authors present an effective multiple deep features learning approach for object retrieval in surveillance videos. Based on the discriminative convolutional neural network (CNN), they can learn multiple deep features to comprehensively describe the visual object. To be specific, they utilise the CNN model pre-trained on ImageNet ILSVRC12 and fine-tuned on our dataset to abstract structure information. In addition, they train another CNN model supervised by 11 colour names to deliver the colour information. To improve the retrieval performance, the deep features are encoded into short binary codes by locality-sensitive hash and fused to fast retrieve the object of interest. Retrieval experiments are performed on a dataset of 100k objects extracted from multi-camera surveillance videos. Comparison results with other common visual features show the effectiveness of the proposed approach.
关键词	Object Retrieval Multiple Deep Features Learning Convolutional Neural Network
WOS标题词	Science & Technology ; Technology
DOI	10.1049/iet-cvi.2015.0291
收录类别	SCI
语种	英语
项目资助者	863 Program(2014AA015104) ; National Natural Science Foundation of China(61273034 ; 61332016)
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000380260100005
引用统计	被引频次：17[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/12168
专题	紫东太初大模型研究中心_图像与视频分析
通讯作者	Wang, Jinqiao
作者单位	Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, 95 Zhongguancun East Rd, Beijing, Peoples R China
第一作者单位	模式识别国家重点实验室
通讯作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Guo, Haiyun,Wang, Jinqiao,Lu, Hanqing. Multiple deep features learning for object retrieval in surveillance videos[J]. IET COMPUTER VISION,2016,10(4):268-271.
APA	Guo, Haiyun,Wang, Jinqiao,&Lu, Hanqing.(2016).Multiple deep features learning for object retrieval in surveillance videos.IET COMPUTER VISION,10(4),268-271.
MLA	Guo, Haiyun,et al."Multiple deep features learning for object retrieval in surveillance videos".IET COMPUTER VISION 10.4(2016):268-271.

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