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What Are We Tracking: A Unified Approach of Tracking and Recognition

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3 Author(s)
Jialue Fan ; Northwestern Univ., Evanston, IL, USA ; Xiaohui Shen ; Ying Wu

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.

Published in:

IEEE Transactions on Image Processing  (Volume:22 ,  Issue: 2 )