Multi-object tracking in non-stationary video using bacterial foraging swarms

Author

Nguyen, Hoang Thanh ; Bhanu, Bir

Author_Institution

Center for Res. in Intell. Syst., Univ. of California, Riverside, Riverside, CA, USA

fYear

2009

fDate

7-10 Nov. 2009

Firstpage

877

Lastpage

880

Abstract

One of the key problems in the field of image processing is object tracking in video. Multiple objects, occlusion, and non-stationary video are some of the challenges that one may face in developing an effective approach. A less-studied approach considers swarm intelligence. This paper presents a new and improved algorithm based on Bacterial Foraging Optimization in order to track multiple objects in real-time video exposed to full and partial occlusion, using video from a moving camera. A comparison with various algorithms is provided.

Keywords

cameras; object detection; particle swarm optimisation; tracking; video signal processing; bacterial foraging swarm intelligence; image processing; moving camera; multiobject tracking; nonstationary video; occlusion; Cameras; Computer vision; Convergence; Gaussian noise; Image processing; Microorganisms; Particle filters; Particle swarm optimization; Strontium; Target tracking; multi-object tracking; non-stationary video; swarm intelligence;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing (ICIP), 2009 16th IEEE International Conference on

Conference_Location

Cairo

ISSN

1522-4880

Print_ISBN

978-1-4244-5653-6

Electronic_ISBN

1522-4880

Type

conf

DOI

10.1109/ICIP.2009.5414276

Filename

5414276