Social Force Model-Based MCMC-OCSVM Particle PHD Filter for Multiple Human Tracking

Abstract

Video-based multiple human tracking often involves several challenges, including target number variation, object occlusions, and noise corruption in sensor measurements. In this paper, we propose a novel method to address these challenges based on probability hypothesis density (PHD) filtering with a Markov chain Monte Carlo (MCMC) implementation. More… (More)
DOI: 10.1109/TMM.2016.2638206

14 Figures and Tables

Topics

  • Presentations referencing similar topics