title: What are we tracking: a unified approach of tracking and recognition.
abstract: Tracking is essentially a matching problem. While traditional tracking methods mostly focus on low-level image correspondences between frames, we argue that high-level semantic correspondences are indispensable to make tracking more reliable. Based on that, a unified approach of low-level object tracking and high-level recognition is proposed for single object tracking, in which the target category is actively recognized during tracking. High-level offline models corresponding to the recognized category are then adaptively selected and combined with low-level online tracking models so as to achieve better tracking performance. Extensive experimental results show that our approach outperforms state-of-the-art online models in many challenging tracking scenarios such as drastic view change, scale change, background clutter, and morphable objects.
authors.affiliation: Northwestern University, Evanston, IL 60208, USA. jialue.fan@u.northwestern.edu
authors.forename: Jialue
authors.initials: J
authors.lastname: Fan
authors.forename: Xiaohui
authors.initials: X
authors.lastname: Shen
authors.forename: Ying
authors.initials: Y
authors.lastname: Wu