Face Tracking Based on Particle Filter with Multi-feature Fusion

Zhiyu Zhou, Dichong Wu, Xiaolong Peng, Zefei Zhu, Chuanyu Wu, Jinbin Wu

Abstract


Traditional particle filter cannot accommodate to the environment of background interferences, illumination variations and occlusions. This paper presents a face tracking method with fusion of color histogram, contour features and grey model based on particle filter. First, it brought in contour features as the main cue of multiple features when tracking the face without stable color histogram. Then, as prior information was neglected in traditional particle filter, this paper employed GM(1,1) model to yield proposal distribution, such that the proposal distribution would bear a higher approximation to posterior probability. Finally, in the importance sampling step, sampling was corresponded to the particle weight in case of the particle degradation. The experiments show that our method outperformed the previous with more accuracy and flexibility, particularly under the condition of color background interferences, drastic illumination variations and complete occlusions.

 

DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.3381


Keywords


Face tracking, color histogram, contour features, particle filter, GM(1,1) model

Full Text:

PDF

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

shopify stats IJEECS visitor statistics