Multi-target tracking by using particle filtering and a social force model

Author

Ata-ur-Rehman ; Naqvi, Syed Mohsen ; Mihaylova, Lyudmila ; Chambers, Jonathon A.

Author_Institution

Dept. of Autom. Control & Syst. Eng., Univ. of Sheffield, Sheffield, UK

fYear

2014

fDate

7-10 July 2014

Firstpage

1

Lastpage

6

Abstract

This paper presents a particle filter for multiple target tracking. The main contribution of this work is in the proposed likelihood function accounting for the interactions between the objects. The filter likelihood function is calculated by combining a social force model for human behaviour with image features such as colour and motion. The added social force model contributes to coping with occlusions between the objects. The performance of the developed algorithm is validated on real video data. The results demonstrate the algorithm accuracy during complex interactions between the objects.

Keywords

feature extraction; image colour analysis; image motion analysis; maximum likelihood estimation; particle filtering (numerical methods); target tracking; video signal processing; colour feature; image features; likelihood function; motion feature; multi-target tracking; object interaction; occlusion; particle filtering; social force model; video data; Equations; Force; Histograms; Image color analysis; Mathematical model; Target tracking; multi-target tracking; particle filter; social force model;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Fusion (FUSION), 2014 17th International Conference on

Conference_Location

Salamanca

Type

conf

Filename

6916228