Title
Search Tracker: Human-Derived Object Tracking in the Wild Through Large-Scale Search and Retrieval.
Abstract
Humans use context and scene knowledge to easily localize moving objects in conditions of complex illumination changes, scene clutter, and occlusions. In this paper, we present a method to leverage human knowledge in the form of annotated video libraries in a novel search and retrieval-based setting to track objects in unseen video sequences. For every video sequence, a document that represents motion information is generated. Documents of the unseen video are queried against the library at multiple scales to find videos with similar motion characteristics. This provides us with coarse localization of objects in the unseen video. We further adapt these retrieved object locations to the new video using an efficient warping scheme. The proposed method is validated on in-the-wild video surveillance data sets where we outperform state-of-the-art appearance-based trackers. We also introduce a new challenging data set with complex object appearance changes.
Year
Venue
Field
2017
IEEE Trans. Circuits Syst. Video Techn.
BitTorrent tracker,Computer vision,Data set,Image warping,Pattern recognition,Clutter,Computer science,Video tracking,Human knowledge,Artificial intelligence
DocType
Volume
Issue
Journal
27
8
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Archith John Bency100.34
S. Karthikeyan2396.42
Carter De Leo3262.50
Santhoshkumar Sunderrajan4414.89
B. S. Manjunath57561783.37