报告题目：Interest Points of General Imbalance

报告人：李祺

主持人：沈超敏

时间：2013年1月15日（星期二）上午10点30分

地点：中山北路校区理科大楼A207会议室

报告摘要: The imbalance oriented selection scheme was recently introduced to detect stable interest points in weakly or sparsely textured images. The scheme chooses image points whose one-pixel-wide directional intensity variations can be clustered into two imbalanced classes as candidates. An important property of imbalance oriented selection is that imbalanced points can be contiguous to others, i.e., imbalanced points have local geometry coherent property. In this paper, we propose general imbalance decided by multipixel-wide directional intensity variations. We give a theoretical analysis on a relation between imbalance and general imbalance. In terms of the local geometry coherent property of general imbalanced points, we propose a global-to-local appearance based matching scheme for imbalanced point correspondence. Last, we present an application of general imbalanced points to road sign detection, which demonstrates the good potential of general imbalanced points.

报告人简介: 李祺博士是美国Western Kentucky University 计算机系的副教授, NeuroComputing杂志的Associate Editor. 李祺副教授的研究领域主要包括Data mining, Machine learning, Bioinformatics 和Appearance based recognition. 他在IEEE Trans. on Image Processing 等一流杂志和IEEE Conf. on Computer Vision and Pattern Recognition等一流会议上发表论文40多篇.