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» Local Features for Object Class Recognition
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PAKDD
2005
ACM
133views Data Mining» more  PAKDD 2005»
14 years 1 months ago
Feature Selection for High Dimensional Face Image Using Self-organizing Maps
: While feature selection is very difficult for high dimensional, unstructured data such as face image, it may be much easier to do if the data can be faithfully transformed into l...
Xiaoyang Tan, Songcan Chen, Zhi-Hua Zhou, Fuyan Zh...
DICTA
2009
13 years 8 months ago
SIFTing the Relevant from the Irrelevant: Automatically Detecting Objects in Training Images
Many state-of-the-art object recognition systems rely on identifying the location of objects in images, in order to better learn its visual attributes. In this paper, we propose fo...
Edmond Zhang, Michael Mayo
ICIAR
2010
Springer
14 years 13 days ago
Adaptation of SIFT Features for Robust Face Recognition
Abstract. The Scale Invariant Feature Transform (SIFT) is an algorithm used to detect and describe scale-, translation- and rotation-invariant local features in images. The origina...
Janez Krizaj, Vitomir Struc, Nikola Pavesic
CVPR
2010
IEEE
14 years 4 months ago
Global and Efficient Self-Similarity for Object Classification and Detection
Self-similarity is an attractive image property which has recently found its way into object recognition in the form of local self-similarity descriptors [5, 6, 14, 18, 23, 27] In...
Thomas Deselaers, Vittorio Ferrari
TIP
2008
287views more  TIP 2008»
13 years 7 months ago
3-D Object Recognition Using 2-D Views
We consider the problem of recognizing 3-D objects from 2-D images using geometric models and assuming different viewing angles and positions. Our goal is to recognize and localize...
Wenjing Li, George Bebis, Nikolaos G. Bourbakis