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MLDM
2005
Springer
15 years 11 months ago
Unsupervised Learning of Visual Feature Hierarchies
We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
Fabien Scalzo, Justus H. Piater
ECCV
2006
Springer
16 years 8 months ago
Region Covariance: A Fast Descriptor for Detection and Classification
We describe a new region descriptor and apply it to two problems, object detection and texture classification. The covariance of d-features, e.g., the three-dimensional color vecto...
Oncel Tuzel, Fatih Porikli, Peter Meer
CVPR
2010
IEEE
16 years 1 months ago
Scale-Hierarchical 3D Object Recognition in Cluttered Scenes
3D object recognition in scenes with occlusion and clutter is a difficult task. In this paper, we introduce a method that exploits the geometric scale-variability to aid in this ...
Prabin Bariya, Ko Nishino
CVPR
2007
IEEE
16 years 8 months ago
Capturing long-range correlations with patch models
The use of image patches to capture local correlations between pixels has been growing in popularity for use in various low-level vision tasks. There is a trade-off between using ...
Vincent Cheung, Nebojsa Jojic, Dimitris Samaras
ICCV
1995
IEEE
15 years 9 months ago
Recognizing 3D Objects Using Photometric Invariant
In this paper we describe a new e cient algorithm for recognizing 3D objects by combining photometric and geometric invariants. Some photometric properties are derived, that are i...
Kenji Nagao