By Topic

Detection and Tracking of Multiple Moving Objects in Real-World Scenarios using Attributed Relational Graph

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Wei Huang ; Dept. of Electr. & Comput. Eng., Univ. of Windsor, Windsor, ON ; Wu, Q.M.J.

This paper presents a new algorithm for detecting and tracking multiple moving objects in both outdoor and indoor environments. The proposed method measures the change of a combined color-texture feature vector in each image block to detect moving objects. The texture feature is extracted from DCT frequency domain. An attributed relational graph (ARG) is used to represent each object, in which vertices are associated to an objectpsilas sub-regions and edges represent spatial relations among them. Multiple cues including color, texture, and spatial position are integrated to describe each objectpsilas sub-regions. Object tracking and identification are accomplished by inexact graph matching, which enables us to track partially occluded objects and to cope with object articulation. An ARG adaptation scheme is incorporated into the system to handle the changes in object scale and appearance. The experimental results prove the efficiency of the proposed method.

Published in:

Computer and Robot Vision, 2008. CRV '08. Canadian Conference on

Date of Conference:

28-30 May 2008