Abstract:
Level set-based contour tracking methods have generated recent interest in the computer vision community. In this paper, we propose a novel level set-based algorithm for ...Show MoreMetadata
Abstract:
Level set-based contour tracking methods have generated recent interest in the computer vision community. In this paper, we propose a novel level set-based algorithm for tracking dynamic implicit contours that utilizes minimal prior information. Our solution consists of two main steps. In the first step, a simple first-order Markov chain model is employed for the coarse localization of a target object. In the second step, we evolve level sets within a narrow band to accurately track the target contour. Narrow band curve evolution is guided through color- and region-based terms in the standard Chan-Vese framework. Comprehensive experimentation on a dataset comprising of several publicly available video sequences clearly demonstrate the advantage of the proposed tracking algorithm.
Date of Conference: 04-08 December 2016
Date Added to IEEE Xplore: 24 April 2017
ISBN Information: