Multiresolution elastic matching
Computer Vision, Graphics, and Image Processing
On the Verification of Hypothesized Matches in Model-Based Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structural Indexing: Efficient 3-D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
A framework for spatiotemporal control in the tracking of visual contours
International Journal of Computer Vision
Robust multiple car tracking with occlusion reasoning
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
An introduction to genetic algorithms
An introduction to genetic algorithms
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Edge Detection with Embedded Confidence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometric Hashing: An Overview
IEEE Computational Science & Engineering
Distortion Invariant Object Recognition in the Dynamic Link Architecture
IEEE Transactions on Computers
ICONDENSATION: Unifying Low-Level and High-Level Tracking in a Stochastic Framework
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparison of Five Color Models in Skin Pixel Classification
RATFG-RTS '99 Proceedings of the International Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems
Locating objects using the Hausdorff distance
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Object Localization by Bayesian Correlation
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Maintaining Multi-Modality through Mixture Tracking
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Robust Real-Time Face Detection
International Journal of Computer Vision
Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrating Region and Boundary Information for Improved Spatial Coherencein Object Tracking
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 1 - Volume 01
Integral Histogram: A Fast Way To Extract Histograms in Cartesian Spaces
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Tracking Multiple Mouse Contours (without Too Many Samples)
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Point matching as a classification problem for fast and robust object pose estimation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Tracking of multiple objects using optical flow based multiscale elastic matching
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
Effective appearance model and similarity measure for particle filtering and visual tracking
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Pose robust face tracking by combining view-based AAMs and temporal filters
Computer Vision and Image Understanding
Hand tracking using optical-flow embedded particle filter in sign language scenes
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
Neurocomputing
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The design and implementation of a multiple face tracking framework that integrates face detection and face tracking is presented. Specifically, the incorporation of a novel proposal distribution and object shape model within the face tracking framework is proposed. A general solution that incorporates the most recent observation in the proposal distribution using a multiscale elastic matching-based optical flow algorithm is proposed. The proposed multiscale elastic matching-based optical flow algorithm is shown to be general and powerful in three significant ways. First, it allows for the tracking of both, rigid and elastic objects. Second, it enables robust tracking even in the face of sudden and gradual changes in illumination, scale and viewpoint. Third, it is suitable for tracking using both, fixed cameras and moving cameras. The proposed object shape model is based on a kernel-based line segment matching algorithm, which incorporates a voting scheme similar to the Radon Transform. The incorporation of the object shape model is shown to improve the computational complexity and accuracy of the face tracking algorithm and also enhance its robustness to occlusion, noise and scene clutter. Efficient techniques for particle sampling based on the Genetic Algorithm and for computation of the region-based likelihood function using the integral image are proposed. The incorporation of face detection within the face tracking algorithm is also proposed. Experimental results show that the proposed face tracking system is very robust in its ability to handle occlusion, noise, scene clutter and changes in illumination, scale and viewpoint and is also computationally efficient.