Scale Adaptive Ensemble Tracking

摘要：

Visual tracking is treated as a binary classification problem in recent trend. In this paper, we propose a novel approach to preprocess pixel-based examples used for training and online updating of classifiers, resulting in a label map that plays a guidance role, which can greatly alleviate the problem of model degradation and at the same time offer a convenient way to scale adaptation of model templates during the tracking process. An integrated tracking system is built through fusing our method into the ensemble tracking framework. Experiments on challenging video sequences demonstrate the effectiveness of the proposed approach.

关键词： visual tracking label map AdaBoost ensemble scale adaptation

作者: Guanbin Li Hefeng Wu

作者单位: School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China, 510006 National Engineering Research Center of Digital Life, Sun Yat-sen University, Guangzhou, China, 510006

会议类型: 国际会议

会议名称: 2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)

会议地点: 上海

会议语种:英文

页码: 441-445

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）