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80
Voted
ICPR
2002
IEEE
16 years 19 hour 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
113
Voted
ICIP
2004
IEEE
16 years 16 days ago
Decomposition of range images using markov random fields
This paper describes a computational model for deriving a decomposition of objects from laser rangefinder data. The process aims to produce a set of parts defined by compactness a...
Andreas Pichler, Robert B. Fisher, Markus Vincze
100
Voted
DAGM
2008
Springer
15 years 21 days ago
MAP-Inference for Highly-Connected Graphs with DC-Programming
The design of inference algorithms for discrete-valued Markov Random Fields constitutes an ongoing research topic in computer vision. Large state-spaces, none-submodular energy-fun...
Jörg H. Kappes, Christoph Schnörr
110
Voted
ICIP
2002
IEEE
16 years 16 days ago
Robust video text segmentation and recognition with multiple hypotheses
A method for segmenting and recognizing text embedded in video and images is proposed in this paper. In the method, multiple segmentation of the same text region is performed, thu...
Jean-Marc Odobez, Datong Chen
121
Voted
CVPR
2007
IEEE
15 years 9 months ago
Partially Occluded Object-Specific Segmentation in View-Based Recognition
We present a novel object-specific segmentation method which can be used in view-based object recognition systems. Previous object segmentation approaches generate inexact results ...
Minsu Cho (Seoul National University), Kyoung Mu L...