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An Improved Fast Compressive Tracking Algorithm Based on Online Random Forest Classifier
2016
MATEC Web of Conferences
The fast compressive tracking (FCT) algorithm is a simple and efficient algorithm, which is proposed in recent years. But, it is difficult to deal with the factors such as occlusion, appearance changes, pose variation, etc in processing. The reasons are that, Firstly, even if the naive Bayes classifier is fast in training, it is not robust concerning the noise. Secondly, the parameters are required to vary with the unique environment for accurate tracking. In this paper, we propose an improved
doi:10.1051/matecconf/20165901003
fatcat:py26xmma6rdmbduiifnz3omcwu