Occlusion Object Detection via Collaborative Sensing Deep Convolution Network

doi:10.1109/ACPR.2017.90

CORC > 兰州理工大学 > 兰州理工大学 > 新能源学院

	Occlusion Object Detection via Collaborative Sensing Deep Convolution Network
	Li, Ce; Zhao, Xinyu; Liu, Hao; Xiao, Limei
	2017
关键词	occlusion object detection collaboretive sensing deep convolution network
DOI	10.1109/ACPR.2017.90
页码	196-201
英文摘要	Object detection is one of the important problems in computer vision. But external occlusion often cause object features missing which lead to a big challenge of object detection. Aim at the problem of occlusion object detection and try to describe object features more effectively; we proposed a collaborative sensing deep convolution network to achieve co-detection by global and partial features of objects. Firstly, we divide the global and partial of the object, it means we segment parent and child in an object. Then, the joint detection network of parent and child is constructed. Finally, through the collaborative detection we achieve the precise positioning and recognition about parents. The proposed algorithm effectively solves the problem that object can not be detected due to missing features. We also ensure the accuracy of parent construction by child. Experiment results demonstrate that our algorithm performs better than other state-of-the-art methods.
会议录	PROCEEDINGS 2017 4TH IAPR ASIAN CONFERENCE ON PATTERN RECOGNITION (ACPR)
会议录出版者	IEEE
会议录出版地	345 E 47TH ST, NEW YORK, NY 10017 USA
语种	英语
资助项目	National Natural Science Foundation (NSFC) of China[61365003] ; Gansu Province Basic Research Innovation Group Project[1506RJIA031]
WOS研究方向	Computer Science
WOS记录号	WOS:000455581900034
内容类型	会议论文
源URL	[http://119.78.100.223/handle/2XXMBERH/36248]
专题	新能源学院电气工程与信息工程学院
通讯作者	Li, Ce
作者单位	Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou 730050, Gansu, Peoples R China
推荐引用方式 GB/T 7714	Li, Ce,Zhao, Xinyu,Liu, Hao,et al. Occlusion Object Detection via Collaborative Sensing Deep Convolution Network[C]. 见:.