Title :
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
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;
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2009.5414276
