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131
Voted
CVPR
2008
IEEE
16 years 5 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 ...
179
Voted
ICCV
2007
IEEE
16 years 5 months ago
Real-Time Visibility-Based Fusion of Depth Maps
We present a viewpoint-based approach for the quick fusion of multiple stereo depth maps. Our method selects depth estimates for each pixel that minimize violations of visibility ...
Paul Merrell, Amir Akbarzadeh, Liang Wang, Philipp...
ICCV
2005
IEEE
16 years 5 months ago
A Supervised Learning Framework for Generic Object Detection in Images
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
Saad Ali, Mubarak Shah
126
Voted
ICCV
2001
IEEE
16 years 5 months ago
Reconstructing Surfaces Using Anisotropic Basis Functions
Point sets obtained from computer vision techniques are often noisy and non-uniform. We present a new method of surface reconstruction that can handle such data sets using anisotr...
Huong Quynh Dinh, Greg Turk, Gregory G. Slabaugh
ICCV
1999
IEEE
16 years 5 months ago
Fluid Motion Recovery by Coupling Dense and Parametric Vector Fields
In this paper we address the problem of estimating and analyzing the motion in image sequences that involve fluid phenomena. In this context standard motion estimation techniques ...
Étienne Mémin, Patrick Pérez
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