Object/Target tracking is a crucial component of many vision systems. Object tracking issues are overviewed, e.g., occlusion handling, feature loss, drifting to the backgound. Many approaches regarding person/object detection and tracking in videos have been proposed. In this lecture, video tracking methods using correlation filters or convolutional neural networks are presented, focusing on video trackers that are capable of achieving real-time performance for long-term tracking on embedded computing platforms. Joint object detection and tracking methods are detailed. Tracking performance metrics are overviewed.
