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» Unsupervised Learning of Object Deformation Models
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CVPR
2008
IEEE
14 years 6 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
CVPR
2005
IEEE
14 years 6 months ago
A Statistical Field Model for Pedestrian Detection
This paper presents a new statistical model for detecting and tracking deformable objects such as pedestrians, where large shape variations induced by local shape deformation can ...
Ying Wu, Ting Yu, Gang Hua
NIPS
2004
13 years 6 months ago
The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces
We present an unsupervised algorithm for registering 3D surface scans of an object undergoing significant deformations. Our algorithm does not need markers, nor does it assume pri...
Dragomir Anguelov, Praveen Srinivasan, Hoi-Cheung ...
CVPR
2008
IEEE
14 years 6 months ago
Local deformation models for monocular 3D shape recovery
Without a deformation model, monocular 3D shape recovery of deformable surfaces is severly under-constrained. Even when the image information is rich enough, prior knowledge of th...
Mathieu Salzmann, Raquel Urtasun, Pascal Fua
UAI
2004
13 years 6 months ago
Recovering Articulated Object Models from 3D Range Data
We address the problem of unsupervised learning of complex articulated object models from 3D range data. We describe an algorithm whose input is a set of meshes corresponding to d...
Dragomir Anguelov, Daphne Koller, Hoi-Cheung Pang,...