Open AccessA Hybrid Surf-Based Tracking Algorithm with Online Template Generation
Author(s) -
Anshul Pareek*,
Nidhi Arora
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.l3205.1081219
Subject(s) - bittorrent tracker , computer vision , computer science , artificial intelligence , tracking (education) , kalman filter , algorithm , point (geometry) , mean shift , eye tracking , pattern recognition (psychology) , mathematics , psychology , pedagogy , geometry
Visual tracking is the most challenging fields in the computer vision scope. Occlusion full or partial remains to be a big mile stone to achieve .This paper deals with occlusion along with illumination change, pose variation, scaling, and unexpected camera motion. This algorithm is interest point based using SURF as detector descriptor algorithm. SURF based Mean-Shift algorithm is combined with Lukas-Kanade tracker. This solves the problem of generation of online templates. These two trackers over the time rectify each other, avoiding any tracking failure. Also, Unscented Kalman Filter is used to predict the location of target if target comes under the influence of any of the above mentioned challenges. This combination makes the algorithm robust and useful when required for long tenure of tracking. This is proven by the results obtained through experiments conducted on various data sets.