Real time occlusion handling using Kalman Filter and mean-shift

Author

Panahi, Rahim ; Gholampour, Iman ; Jamzad, Mansour

Author_Institution

Dept. Electr. Eng., Sharif Univ., Tehran, Iran

fYear

2013

Firstpage

320

Lastpage

323

Abstract

Tracking objects using Mean Shift algorithm fails when there is a full/partial occlusion or when the background color and the desired object are close. In this paper we proposed a method using Kalman Filter and Mean Shift for handling these situations. Using similarity measure of Mean Shift algorithm we are able to detect an occlusion. Kalman Filter comes into the play for occlusion handling in a Buffer-Mode Process. We implemented this algorithm both on PC and DSP 64x+ Texas Instrument and the results are both tabulated. The results reveal the ability of our method to locate the object soon after occlusion disappearance.

Keywords

Kalman filters; image colour analysis; object tracking; Kalman filter; background color; buffer-mode process; mean shift algorithm; object tracking; occlusion detection; real time occlusion handling; similarity measure; Equations; Image color analysis; Kalman filters; Mathematical model; Object tracking; Prediction algorithms; Target tracking; DSP Processors; Kalman Filter; MeanShift; Occlusion handling; Prediction; Tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Vision and Image Processing (MVIP), 2013 8th Iranian Conference on

Conference_Location

Zanjan

ISSN

2166-6776

Print_ISBN

978-1-4673-6182-8

Type

conf

DOI

10.1109/IranianMVIP.2013.6780003

Filename

6780003