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.
['Alireza Tavakkoli', 'Mircea Nicolescu', 'George Bebis']
A spatio-spectral algorithm for robust and scalable object tracking in videos