【15-15期VALSE Webinar活动】 报告嘉宾1：冯伟（天津大学）
主持人：操小春（中科院信工所）
报告题目：Superpixel Gridization for Fast Object Localization http://valser.org/webinar/slide/slides/20150520/Wei_Feng_Valse_Webinar20150520.pdf 报告时间：2015年5月20日晚20:00（北京时间）
文章信息：Liang Li, Wei Feng*, Liang Wan, and Jiawan Zhang, Maximum Cohesive Grid of Superpixels for Fast Object Localization, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’2013).
报告简介：To pursue efficiency, accuracy and scalability in large-scale image analysis, which form the fundamental requirements of Big Data, many recent algorithms in computer vision and media computing are built upon superpixels. Compared to the regularly sampled image pixels, the most advantages of superpixels are their good accordance to object boundaries and the considerably reduced number of variables that need to be handled. Hence, superpixel-based approaches usually have much better efficiency and scalability than pixel-level methods, but with comparable or better accuracy. However, the significant irregularity in the topological connections of superpixels encumbers direct applicaton of some successful efficient techniques in pixel-level processing, such as integral image and efficient subwindow search (ESS) etc., to the superpixel-level. This indeed becomes one major bottleneck of superpixel-level image processing. In this work, we focus on optimally regularizing superpixels with arbitrary topological structures into the regular grid structures, based on the scheme of cascade dynamic programming (CDP). We will specifically discuss the generic model of superpixel gridization, feasible initialization and fast optimization methods for superpixel gridization. We will also explore the application of superpixel grid in fast object localization and segmentation. Super pixel gridization will help to promote the seamless transition from pixel-level image processing to superpixel-level processing, by unleashing the great potentials of superpixel-based approaches.
报告人简介：Wei Feng received the B.S. and M.Phil. degrees in Computer Science from Northwestern Polytechnical University, China, in 2000 and 2003 respectively, and the Ph.D. degree in Computer Science from City University of Hong Kong in 2008. From 2008 to 2010, he worked as research fellow at the Chinese University of Hong Kong and City University of Hong Kong, respectively. He is an associate professor in School of Computer Science and Technology and the director of Computer Vision and Media Computing Center of Tianjin University. His major research interest is media computing, specifically including general Markov Random Fields modeling, discrete/continuous energy minimization, image segmentation, semi-supervised clustering, structural authentication, and generic pattern recognition. He has published more than 50 academic papers, including TPAMI, IJCV, TIP, PR, CVPR and ICCV. He got the support of the Program for New Century Excellent Talents in University, China, in 2011. | 