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» Learning Shape Prior Models for Object Matching
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ECCV
1998
Springer
14 years 10 months ago
A Two-Stage Probabilistic Approach for Object Recognition
Assume that some objects are present in an image but can be seen only partially and are overlapping each other. To recognize the objects, we have to rstly separate the objects from...
Stan Z. Li, Joachim Hornegger
ECCV
2010
Springer
14 years 1 months ago
Weakly Supervised Shape Based Object Detection with Particle Filter
Abstract. We describe an efficient approach to construct shape models composed of contour parts with partially-supervised learning. The proposed approach can easily transfer parts ...
ICCV
2007
IEEE
14 years 10 months ago
An Empirical Study of Object Category Recognition: Sequential Testing with Generalized Samples
In this paper we present an empirical study of object category recognition using generalized samples and a set of sequential tests. We study 33 categories, each consisting of a sm...
Liang Lin, Shaowu Peng, Jake Porway, Song Chun Zhu...
ISVC
2005
Springer
14 years 2 months ago
Self-organizing Deformable Model: A New Method for Fitting Mesh Model to Given Object Surface
This paper presents a new method for projecting a mesh model of a source object onto a surface of an arbitrary target object. A deformable model, called Self-organizing Deformable ...
Ken'ichi Morooka, Hiroshi Nagahashi
CVPR
2008
IEEE
14 years 10 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 ...