Object Contour Tracking Using Foreground and Background Distribution Matching

Authors:
Mohand Saïd Allili
Affiliations:
Département d'Informatique et d'Ingénierie, Université du Québec en Outaouais, Gatineau J8X 3X7
Venue:
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Year:
2009

Citing 8
Cited 0

Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations

Journal of Computational Physics
Kernel-Based Object Tracking

IEEE Transactions on Pattern Analysis and Machine Intelligence
Ensemble Tracking

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Online Selection of Discriminative Tracking Features

IEEE Transactions on Pattern Analysis and Machine Intelligence
Globally adaptive region information for automatic color-texture image segmentation

Pattern Recognition Letters
Object tracking in videos using adaptive mixture models and active contours

Neurocomputing
Performance evaluation of object detection algorithms for video surveillance

IEEE Transactions on Multimedia
Active contours for tracking distributions

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we propose an effective approach for tracking distribution of objects. The approach uses a competition between a tracked objet and background distributions using active contours. Only the segmentation of the object in the first frame is required for initialization. The object contour is tracked by assigning pixels in a way that maximizes the likelihood of the object versus the background. We implement the approach using an EM-like algorithm which evolves the object contour exactly to its boundaries and adapts the distribution parameters of the object and the background to data.