title: Robust Object Tracking Using Valid Fragments Selection.
abstract: Local features are widely used in visual tracking to improve robustness in cases of partial occlusion, deformation and rotation. This paper proposes a local fragment-based object tracking algorithm. Unlike many existing fragment-based algorithms that allocate the weights to each fragment, this method firstly defines discrimination and uniqueness for local fragment, and builds an automatic pre-selection of useful fragments for tracking. Then, a Harris-SIFT filter is used to choose the current valid fragments, excluding occluded or highly deformed fragments. Based on those valid fragments, fragment-based color histogram provides a structured and effective description for the object. Finally, the object is tracked using a valid fragment template combining the displacement constraint and similarity of each valid fragment. The object template is updated by fusing feature similarity and valid fragments, which is scale-adaptive and robust to partial occlusion. The experimental results show that the proposed algorithm is accurate and robust in challenging scenarios.
authors.affiliation: Beijing Key Laboratory of Digital Media, School of Computer Science and Engineering, Beihang University, Beijing 100191, China; State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China.
authors.forename: Jin
authors.initials: J
authors.lastname: Zheng
authors.affiliation: Beijing Key Laboratory of Digital Media, School of Computer Science and Engineering, Beihang University, Beijing 100191, China; State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China.
authors.forename: Bo
authors.initials: B
authors.lastname: Li
authors.affiliation: Beijing Key Laboratory of Digital Media, School of Computer Science and Engineering, Beihang University, Beijing 100191, China.
authors.forename: Peng
authors.initials: P
authors.lastname: Tian
authors.affiliation: Schepens Eye Research Institute, Mass Eye and Ear, Harvard Medical School, Boston, MA 02114, USA.
authors.forename: Gang
authors.initials: G
authors.lastname: Luo
keywords: Fragments-based tracking; Harris-SIFT filter; Structured fragments; Template update; Valid fragment selection