Survey of Generative and Discriminative Appearance Models in Visual Object Tracking
K. R. Remya, C Vipin Krishnan · International journal of advance research, ideas and innovations in technology · 2018
Visual object tracking is a challenging task in computer vision applications. The basic statistical appearance modeling techniques are discriminative and generative. In both cases, online learning is very essential to nullify the error due to large pose changes, illumination variations and appearance changes of the tracking framework. This paper briefly introduces the challenges and applications of visual tracking and focuses on discussing the state-of-the-art online-learning based tracking methods by category. In this paper, the existing statistical schemes for tracking-by-detection are reviewed according to their appearance model creation mechanism; generative and discriminative.