CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach
Elliptical Head Tracking Using Intensity Gradients and Color Histograms
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Applying the particle swarm optimizer to non-stationary environments
Applying the particle swarm optimizer to non-stationary environments
Detection and Tracking of Moving Objects from a Moving Platform in Presence of Strong Parallax
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
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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.