Constrained Restoration and the Recovery of Discontinuities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual learning and recognition of 3-D objects from appearance
International Journal of Computer Vision
Probabilistic Visual Learning for Object Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation
International Journal of Computer Vision
Mixtures of probabilistic principal component analyzers
Neural Computation
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift, Mode Seeking, and Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dense Stereo Matching Using Kernel Maximum Likelihood Estimation
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Robust Registration and Tracking Using Kernel Density Correlation
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 11 - Volume 11
Journal of Cognitive Neuroscience
Deterministic edge-preserving regularization in computed imaging
IEEE Transactions on Image Processing
Representing images of a rotating object with cyclic permutation for view-based pose estimation
Computer Vision and Image Understanding
Pattern Recognition Letters
Pattern Recognition Letters
Dynamics of a mean-shift-like algorithm and its applications on clustering
Information Processing Letters
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We present an original appearance model that generalizes the usual Gaussian visual subspace model to non-Gaussian and nonparametric distributions. It can be useful for the modeling and recognition of images under difficult conditions such as large occlusions and cluttered backgrounds. Inference under the model is efficiently solved using the mean shift algorithm.