Robust Color Histograms for Particle Filter Tracking

• Main Authors: Chi-Hung Tang, 湯騏鴻
• Other Authors: Hwann-Tzong Chen
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/24696465548686256255

碩士 === 國立清華大學 === 資訊工程學系 === 95 === Video object tracking is a very important issue in computer vision applications, such as video surveillance, perceptual user interfaces, and object-based video compression. The difficulty of video object tracking might come from many factors, such as cluttered background, occlusions, lighting changes and deformation. In this thesis, we assume that color features in the neighborhood of interest points are important, and propose to use a robust color histogram based on SURF. As shown in the experimental results, the robust color histogram performs well in several difficult scenarios, such as lighting changes and occlusions. Moreover, we use the robust color histogram as the appearance model of the target object to assist video object tracking. We modify the traditional particle filter framework and view each SURF interest point as a particle to develop a new object tracking algorithm. In the experimental results, we have shown that the performance of our object tracking algorithm is good.