Interactive Feedback for Video Tracking Using a Hybrid Maximum Likelihood Similarity Measure

摘要

In this article, we present an object tracking system which allows interactive user feedback to improve the accuracy of the tracking process in real-time video. In addition, we describe the hybrid maximum likelihood similarity, which integrates traditional metrics with the maximum likelihood estimated metric. The hybrid similarity measure is used to improve the dynamic relevance feedback process between the human user and the objects detected by our system.