关键词: 实时压缩跟踪, 随机测量矩阵, 低维特征

Abstract: An advanced Real-time Compressive Tracking（RCT） is proposed. By analyzing low-dimensional features, an advanced random measurement matrix is designed based on RCT, which gives a balanced reflecting to gray level features and texture features. Low-dimensional feature vectors are transformed by using the advanced random measurement matrix. Then it classifies the image sequence into two categories（foreground and background） by using Naive Bayes Classifier. Thus, the tracking of the target is realized. Making a comparison among CT, BCT（a known improved algorithm based on CT） and RCT, according to tracking simulation results to different image sequences, it turns out that RCT shows very robust tracking results without losing the real-time character.

Key words: Real-time Compressive Tracking（RCT）, random measurement matrix, low-dimensional feature vectors