講座題目：Recent Developments in Motion Segmentation and Human Activity Recognition人類活動識別和運動分割的研究進展
講座地點：計算機科學與軟件學院102會議室
講座時間：2015年4月24日（星期五）上午9:30
武慶明教授簡介：
武慶明（Q.M. Jonathan Wu） 教授長期從事計算機視覺，圖像處理，模式識別與智能系統的教學與研究工作，先后主持完成加拿大國家科學與工程研究項目(NSERC)，國際合作重大項目、加拿大國家重點基金項目，現任加拿大溫莎大學電子工程系教授，博士生導師，計算機視覺和傳感系統研究所主任,加拿大汽車電子和信息系統領域首席科學家，至今共培養博士、博士后30 余人，現任國際雜志《IEEE Transaction on Neural Networks and Learning Systems》, 《InternationalJournal of Robotics and Automation》與《Cognitive Computation》副主編，《IEEE Computational Intelligence Magazine》客座編委。曾任《IEEE Transaction on Systems, Man, and Cybernetics, Part A》與《International Journal of Control and Automation》編委。在過去的研究工作中，申請人對圖像實時分割、圖像壓縮與特征提取、圖像去噪與識別、三維重建等問題進行了深入研究，其研究成果均以通訊作者發表于《IEEE Transactions on Neural Networks and Learning Systems》、《IEEE Transactions on Image Processing》、《IEEE Transactions on Cybernetics》、《IEEE Transactions on Fuzzy Systems》、《International Journal of Computer Vision》、《Pattern Recognition》等國際相關學術期刊上，其中SCI 收錄論文100 多篇， IEEE Transactions 論文40 余篇，在圖像處理、智能信息處理、機器學習與模式識別領域，取得多項重大研究成果。武教授多次參加并任職包括ICCV、CVPR、ACCV、ICIP 等在內三十多個國際會議的組織委員會主席和評審委員會委員。
講座內容簡介：
Motion segmentation in terms of dynamic textures, and human activity recognition are topics that have attracted growing attention in computer vision community. This talk is mainly concentrated on recent trends in dynamic texture segmentation, and human activity recognition. We first present two techniques for dynamic texture: a feature selection based dynamic mixture model for motion segmentation, and a linear-time video segmentation method which is scalable and temporally consistent for streaming videos. We then present a general framework to efficiently identify objects of interest in still images and later extend its application to human action recognition in videos. Such scheme can also be implemented in a situation where training data is coming in a serial mode and training needs to be performed in an incremental fashion. A brief overview of other related research activities in the presenter’s laboratory is also provided. Applications have been extended towards intelligent transportation systems, surveillance and security, face and gesture recognition, vision-guided robotics, and biomedical imaging, among others.
