A spatio-spectral algorithm for robust and scalable object tracking in videos

Authors:
Alireza Tavakkoli;Mircea Nicolescu;George Bebis
Affiliations:
Computer Science Department, University of Houston-Victoria, Victoria, TX;Computer Science and Engineering Department, University of Nevada, Reno, NV;Computer Science and Engineering Department, University of Nevada, Reno, NV and Computer Science Department, King Saud University, Riyadh, Saudi Arabia
Venue:
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part III
Year:
2010

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Abstract

In this work we propose a mechanism which looks at processing the low-level visual information present in video frames and prepares mid-level tracking trajectories of objects of interest within the video. The main component of the proposed framework takes detected objects as inputs and generates their appearance models, maintains them and tracks these individuals within the video. The proposed object tracking algorithm is also capable of detecting the possibility of collision between the object trajectories and resolving it without losing their models.