Your browser does not support JavaScript!

Improved mean shift algorithm for occlusion pedestrian tracking

Improved mean shift algorithm for occlusion pedestrian tracking

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
Electronics Letters — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Occlusion pedestrian tracking is still a difficult problem in video surveillance, while traditional mean shift tracking algorithms fail to track these kinds of targets. Proposed is an improved mean shift tracking approach to solve this problem. Two aspects are improved for the traditional mean shift tracking algorithm. First, occlusion layers are used to represent pedestrian occlusion relation and the non-occlusion part of each pedestrian which is obtained according to occlusion relation is used for the mean shift tracking algorithm. Secondly, the states of the related occlusion pedestrians are gradually adjusted one by one to eliminate the occlusion effect, during the tracking process. The contrast experiment results show that the improved algorithm is real time for well tracking the occlusion pedestrians which cannot be tracked by the traditional mean shift tracking algorithm.


    1. 1)
    2. 2)
      • F.J. Lv , T. Zhao , R. Nevatia . Camera calibration from video of a walking human. IEEE Trans. Pattern Anal. Mach. Intell. , 28 , 1513 - 1518
    3. 3)
      • Comaniciu, D., Ramesh, V., Meer, P.: `Real-time tracking of non-rigid objects using mean shift', IEEE Conf. on Computer Vision and Pattern Recognition, 2000, South Carolina, 2, p. 142–149.
    4. 4)
      • Wu, Y., Yu, T., Hua, G.: `Tracking appearances with occlusions', IEEE Conf. Computer Vision and Pattern Recognition, June 2003, Madison, Wisconsin, USA, I, p. 789–795.
    5. 5)

Related content

This is a required field
Please enter a valid email address