Tracking and data association
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fitting Parameterized Three-Dimensional Models to Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active vision
Model-based object tracking in monocular image sequences of road traffic scenes
International Journal of Computer Vision
An Active Testing Model for Tracking Roads in Satellite Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pose and structure recovery using active models
BMVC '95 Proceedings of the 1995 British conference on Machine vision (Vol. 1)
3D Pose Estimation by Directly Matching Polyhedral Models to Gray Value Gradients
International Journal of Computer Vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
Edge Detection and Ridge Detection with Automatic Scale Selection
International Journal of Computer Vision
Fundamental Limits of Bayesian Inference: Order Parameters and Phase Transitions for Road Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Efficient deformable template detection and localization without user initialization
Computer Vision and Image Understanding
Numerical Recipes in C: The Art of Scientific Computing
Numerical Recipes in C: The Art of Scientific Computing
The Problem of Sparse Image Coding
Journal of Mathematical Imaging and Vision
Tracking with the EM Contour Algorithm
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Finding Deformable Shapes Using Loopy Belief Propagation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Learning the Statistics of People in Images and Video
International Journal of Computer Vision - Special Issue on Computational Vision at Brown University
3D pose estimation by fitting image gradients directly to polyhedral models
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
A Probabilistic Contour Discriminant for Object Localisation
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Maintaining Multi-Modality through Mixture Tracking
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
International Journal of Computer Vision
Visual Hand Tracking Using Nonparametric Belief Propagation
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 12 - Volume 12
Computer Vision and Image Understanding - Special issue on eye detection and tracking
Comparison of edge-driven algorithms for model-based motion estimation
SCVMA'04 Proceedings of the First international conference on Spatial Coherence for Visual Motion Analysis
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
Primal sketch: Integrating structure and texture
Computer Vision and Image Understanding
On the computational rationale for generative models
Computer Vision and Image Understanding
Initialization of Model-Based Vehicle Tracking in Video Sequences of Inner-City Intersections
International Journal of Computer Vision
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When fitting contour models to image data, it is necessary to take into account unmodelled shape variability. Traditionally, this has been done either by blurring the input image or by looking for image features in the neighborhood of the contour. A more statistically rigorous approach is to marginalize over all possible shape deformations. When this is done, the resulting likelihood model has similarities to both the blurring approach and the feature-based approach. A tracking application is used to demonstrate the marginalized likelihood model and compare it to the blurring approach. The best tracking results were obtained with the new model when combined with the Expectation-Maximization (EM) algorithm.