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Now showing items 11-17 of 17
Transferring Nonlinear Representations using Gaussian Processes with a Shared Latent Space
(2008-04-11)
When a series of problems are related, representations derived from learning earlier tasks may be useful in solving later problems. In this paper we propose a novel approach to transfer learning with low-dimensional, ...
Transfer learning for image classification with sparse prototype representations
(2008-03-03)
To learn a new visual category from few examples, prior knowledge from unlabeled data as well as previous related categories may be useful. We develop a new method for transfer learning which exploits available unlabeled ...
Fast Contour Matching Using Approximate Earth Mover's Distance
(2003-12-05)
Weighted graph matching is a good way to align a pair of shapesrepresented by a set of descriptive local features; the set ofcorrespondences produced by the minimum cost of matching features fromone shape to the features ...
Latent-Dynamic Discriminative Models for Continuous Gesture Recognition
(2007-01-07)
Many problems in vision involve the prediction of a class label for each frame in an unsegmented sequence. In this paper we develop a discriminative framework for simultaneous sequence segmentation and labeling which can ...
Combining Object and Feature Dynamics in Probabilistic Tracking
(2005-03-02)
Objects can exhibit different dynamics at different scales, a property that isoftenexploited by visual tracking algorithms. A local dynamicmodel is typically used to extract image features that are then used as inputsto a ...
Efficient Image Matching with Distributions of Local Invariant Features
(2004-11-22)
Sets of local features that are invariant to common image transformations are an effective representation to use when comparing images; current methods typically judge feature sets' similarity via a voting scheme (which ...
Approximate Correspondences in High Dimensions
(2006-06-15)
Pyramid intersection is an efficient method for computing an approximate partial matching between two sets of feature vectors. We introduce a novel pyramid embedding based on a hierarchy of non-uniformly shaped bins that ...