Hierarchical MRF model for model-based multi-object tracking

Y. Chen, Thomas S Huang

Research output: Contribution to conferencePaperpeer-review

Abstract

To track multiple objects, top-down (model-based methods) and bottom-up (multi-layer analysis) methods have been proposed separately. In this paper, a hierarchical MRF model is proposed to integrate these two trends into a MAP framework for tracking non-rigid objects such as human hands or faces. Parametric models of color, shape and frame difference for both foreground and background are given. Dynamic constraints are used to update the observation models and present an initial segmentation for the new frame. A novel hierarchical MRF model is proposed to efficiently refine the segmentation based on local smoothness constraints. The algorithm does not need to initialize and can detect new moving objects and track them. It can also handle the stopped objects because of the utilization of spatial-temporal constraints. Promising results are reported in this paper.

Original languageEnglish (US)
Pages385-388
Number of pages4
StatePublished - Jan 1 2001
EventIEEE International Conference on Image Processing (ICIP) 2001 - Thessaloniki, Greece
Duration: Oct 7 2001Oct 10 2001

Other

OtherIEEE International Conference on Image Processing (ICIP) 2001
Country/TerritoryGreece
CityThessaloniki
Period10/7/0110/10/01

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Hierarchical MRF model for model-based multi-object tracking'. Together they form a unique fingerprint.

Cite this