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» Statistical Models of Appearance for Computer Vision
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ECCV
2010
Springer
15 years 5 months ago
Localizing Objects while Learning Their Appearance
Learning a new object class from cluttered training images is very challenging when the location of object instances is unknown. Previous works generally require objects covering a...
ICPR
2002
IEEE
16 years 27 days ago
Robust Appearance-Based Object Recognition Using a Fully Connected Markov Random Field
This paper presents a new kernel method for appearance-based object recognition, highly robust to noise and occlusion. It consists of a fully connected Markov Random Field that in...
Barbara Caputo, Sahla Bouattour, Heinrich Niemann
ICPR
2002
IEEE
16 years 27 days ago
Manifold Pursuit: A New Approach to Appearance Based Recognition
Manifold Pursuit (MP) extends Principal Component Analysis to be invariant to a desired group of image-plane transformations of an ensemble of un-aligned images. We derive a simpl...
Amnon Shashua, Anat Levin, Shai Avidan
ICCV
2009
IEEE
16 years 4 months ago
The Dimensionality of Scene Appearance
Low-rank approximation of image collections (e.g., via PCA) is a popular tool in many areas of computer vision. Yet, surprisingly little is known justifying the observation that...
Rahul Garg, Hao Du, Steven M. Seitz, Noah Snavely
ECCV
2006
Springer
15 years 3 months ago
Segmenting Dynamic Textures with Ising Descriptors, ARX Models and Level Sets
Abstract. We present a new algorithm for segmenting a scene consisting of multiple moving dynamic textures. We model the spatial statistics of a dynamic texture with a set of secon...
Atiyeh Ghoreyshi, René Vidal