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» Learning Models for Object Recognition
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ECCV
2008
Springer
14 years 9 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
ACCV
2010
Springer
13 years 2 months ago
Continuous Surface-Point Distributions for 3D Object Pose Estimation and Recognition
We present a 3D, probabilistic object-surface model, along with mechanisms for probabilistically integrating unregistered 2.5D views into the model, and for segmenting model instan...
Renaud Detry, Justus H. Piater
AR
2011
13 years 2 months ago
Learning, Generation and Recognition of Motions by Reference-Point-Dependent Probabilistic Models
This paper presents a novel method for learning object manipulation such as rotating an object or placing one object on another. In this method, motions are learned using referenc...
Komei Sugiura, Naoto Iwahashi, Hideki Kashioka, Sa...
CAIP
1999
Springer
115views Image Analysis» more  CAIP 1999»
14 years 9 hour ago
EigenHistograms: Using Low Dimensional Models of Color Distribution for Real Time Object Recognition
Abstract. Distribution of object colors has been used in computer vision for recognition and indexing. Most of the recent approaches to this problem have been focused on de ning op...
Jordi Vitrià, Petia Radeva, Xavier Binefa
CVPR
2011
IEEE
13 years 3 months ago
Learning Object Color Models from Multi-view Constraints
Color is known to be highly discriminative for many object recognition tasks, but is difficult to infer from uncontrolled images in which the illuminant is not known. Traditional...
Trevor Owens, Kate Saenko, Trevor Darrell, Ayan Ch...