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» Novel image feature alphabets for object recognition
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DICTA
2009
14 years 10 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
DAGM
1997
Springer
15 years 1 months ago
A Feature Map Approach to Real-Time 3-D Object Pose Estimation from Single 2-D Perspective Views
A novel approach to the computation of an approximate estimate of spatial object pose from camera images is proposed. The method is based on a neural network that generates pose hy...
S. Winkler, Patrick Wunsch, Gerd Hirzinger
EPIA
2009
Springer
15 years 1 months ago
Semantic Image Search and Subset Selection for Classifier Training in Object Recognition
Abstract. Robots need to ground their external vocabulary and internal symbols in observations of the world. In recent works, this problem has been approached through combinations ...
Rui Pereira, Luís Seabra Lopes, Augusto Sil...
CCIA
2007
Springer
15 years 4 months ago
An Evaluation of an Object Recognition Schema Using Multiple Region Detectors
Abstract. Robust object recognition is one of the most challenging topics in computer vision. In the last years promising results have been obtained using local regions and descrip...
Meritxell Vinyals, Arnau Ramisa, Ricardo Toledo
MICAI
2010
Springer
14 years 8 months ago
Object Class Recognition Using SIFT and Bayesian Networks
Several methods have been presented in the literature that successfully used SIFT features for object identification, as they are reasonably invariant to translation, rotation, sc...
Leonardo Chang, Miriam Monica Duarte, Luis Enrique...