Real-Time Automatic Target Selection and Tracking Algorithm Using Keypoint-Based Template Matching

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题名:	Real-Time Automatic Target Selection and Tracking Algorithm Using Keypoint-Based Template Matching
作者:	Tsai, Chi-Yi;Yu, Cheng-Jui
关键词:	Keypoint extraction;object detection;mean shift clustering;template matching;visual tracking
日期:	2015-09-05
上传时间:	2016-04-27 11:20:54 (UTC+8)
出版者:	IIAE
摘要:	Object detection and tracking is an important function that helps bringing robots into real-world environments. Detection of an object-of-interest (OOI) from multiple stacking objects still holds certain degree of difficulty. In this paper, a novel target selection and tracking algorithm is proposed for detecting and tracking one OOI from multiple stacking objects. The proposed method first employs a keypoint extraction algorithm to compute control points from incoming images. Next, each OOI appeared in the image is extracted from the multiple stacking objects in a box by using mean shift clustering approach. Finally, a template-based visual tracking method is adopted to locate and track center position of the top OOI in the box. The proposed algorithm had been implemented on an Intel Core i5-4440 3.1GHz platform, achieving real-time performance about 30 frames per second at 640x480 image resolution in the experiments.
關聯:	Proceedings of the 3rd IIAE International Conference on Intelligent Systems and Image Processing 2015, pp.187-190
DOI:	10.12792/icisip2015.036
显示于类别:	[電機工程學系暨研究所] 會議論文

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