Floating-Bagging-Adaboost ensemble for object detection using local shape-based features

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	Floating-Bagging-Adaboost ensemble for object detection using local shape-based features
	Tang XS(唐旭晟); Shi ZL(史泽林); Li DQ(李德强); Ma L(马龙); Chen D(陈丹)
	2009
会议名称	2009 International Conference on Machine Learning and Cybernetics
会议日期	July 12-15, 2009
会议地点	Baoding , China
页码	45-49
中文摘要	We propose a novel learning algorithm, called Bagging-Adaboost ensemble algorithm with floating search algorithm post optimization, for object detection that uses local shape-based feature. The feature use the chamfer distance as a shape comparison measure. It can be calculated very quickly using a look-up table. Random sampling boosting algorithm is used to form an object detector. Floating search post optimization procedure is used to remove base classifiers which cause higher error rates. The resulting classifier consists of fewer base classifiers yet achieves better generalization performance. To demonstrate our method we trained a system to detect pedestrians in complex natural scenes. Experimental results show that our system can extremely rapidly detect objects with high detection rate. The learning techniques can be extended to detect other objects.
收录类别	EI ; CPCI（ISTP）
产权排序	1
会议主办者	IEEE
会议录	2009 International Conference on Machine Learning and Cybernetics
会议录出版者	IEEE
会议录出版地	New York
语种	英语
WOS记录号	WOS:000281720400009
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/7980]
专题	沈阳自动化研究所_光电信息技术研究室
推荐引用方式 GB/T 7714	Tang XS,Shi ZL,Li DQ,et al. Floating-Bagging-Adaboost ensemble for object detection using local shape-based features[C]. 见:2009 International Conference on Machine Learning and Cybernetics. Baoding , China. July 12-15, 2009.