By Topic

Human tracking in the complicated background by Particle Filter using color-histogram and HOG

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

3 Author(s)
Lujun Jin ; Dept. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China ; Jian Cheng ; Hu Huang

Human tracking based on computer vision, is a challenging and crucial problem in intelligent video surveillance system. As is known to all, human motion is usually non-linear and non-Gaussian, many prevalent frameworks are not appropriate, such as Kalman Filter, etc. Nevertheless, the Particle Filter could still have good performance even when the system is nonlinear and non-Gaussian. This paper is based on Particle Filter, too. In many cases, the Particle Filter always uses single-human-feature (such as color-histogram, edge gradient, Histogram of Oriented Gradients (HOG), etc) to track human objects. But using single-human-feature will lose a lot of information in the process of tracking human objects. In order to avoid this drawback, this paper proposes to fuse the information of color-histogram and HOG to track. This method keeps both color and shape information, consequently, it is more robust and steady. Experiment results demonstrate that this method is effective to improve the performance of tracking.

Published in:

Intelligent Signal Processing and Communication Systems (ISPACS), 2010 International Symposium on

Date of Conference:

6-8 Dec. 2010