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                                                                  控制系學術報告:A Comparative Study of Image Feature Detectors and Descriptors
                                                                  時間:2014-04-16 來源:綜合辦 編輯:zhbgs 訪問次數:1919

                                                                  報告題目:A Comparative Study of Image Feature Detectors and Descriptors
                                                                  報告人:Jonathan Wu, University of Windsor, Canada
                                                                  時間: 4月23號 10:00-12:00

                                                                  Abstract :Feature detection and matching is a fundamental problem in many computer and robot vision applications. During the past decades, various types of feature detectors and descriptors have been proposed in the literature.
                                                                  This presentation provides a comparative study of a large number of popular feature detectors from last three decades. The study makes several contributions towards a generic comparison of feature detectors and descriptors. Firstly, comparisons on invariance against image transformations such as illumination changes, blurring, rotation, scaling, viewpoint changes, exposure, JPEG compression, combined scaling and rotation, combined viewpoint changes, scaling, and rotation are conducted. The second contribution of the work is to provide a proper distinction between detectors and descriptors with separate comparisons. Exhaustive experiments on several datasets for each combination of detector and descriptor have been conducted to provide a ranking which can also be weighted to suit specific applications.


                                                                      武慶明(Q.M. Jonathan Wu)教授1990年畢業於英國威爾士-斯旺西大學,獲得電子工程博士學位 。1995年他加入加拿大國家研究院(National Research Council of Canada) ,併成爲高級研究主管。2005年起任教加拿大溫莎大學University of Windsor,現任計算機視覺和傳感系統研究室主任 ,加拿大汽車電子和信息系統的首席科學家。
                                                                      武慶明教授主要從事計算機和機器人視覺,圖像處理, 模式識別和智能系統的研究。武教授已在相關國際學術會議及國際核心期刊上發表學術論文300餘篇 ,其中包括150多篇的國際期刊論文 (50多篇爲IEEE Transaction論文)。武教授曾擔任五十多個國際會議的組織委員會主席和評審委員會委員 ,現任IEEE Transaction on Neural Networks and Learning Systems, IEEE Transaction on Systems, Man, and Cybernetics-Part A 與International Journal of Robotics and Automation的副主編 。