@inbook{e810cfade238435db9a19acfbdd58f4e,
title = "An on-line visual human tracking algorithm using SURF-based dynamic object model",
abstract = "The interest point based tracking methods suffer from the limitation of unavailability of sufficient number of matching key points for the target in all frames of a running video. In this paper, a dynamic model is proposed for describing the object model which is used for tracking a human in a non-stationary video. This dynamic model takes into account the change in the pose as well as the motion of the human. A simple autoregression based predictor is used for dealing with the case of full occlusion. Simulation results are provided to show the efficacy of the algorithm. {\textcopyright} 2013 IEEE.",
keywords = "Auto-regression prediction, Human Tracking, SURF",
author = "Meenakshi Gupta and Sourav Garg and Swagat Kumar and Laxmidhar Behera",
year = "2014",
month = feb,
day = "13",
doi = "10.1109/ICIP.2013.6738798",
language = "English",
isbn = "9781479923410",
series = "2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings",
pages = "3875--3879",
booktitle = "2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings",
note = " 2013 IEEE International Conference on Image Processing ; Conference date: 15-09-2013 Through 19-09-2013",
}