DocumentCode
561175
Title
A Robust Affine Invariant Feature Matching Approach
Author
Gao, Ce ; Song, Yixu ; Jia, Peifa
Author_Institution
Tsinghua Nat. Lab. for Inf. Sci. & Technol., Tsinghua Univ., Beijing, China
Volume
1
fYear
2011
fDate
18-21 Dec. 2011
Firstpage
157
Lastpage
160
Abstract
Affine transformation detection can be used in many computer vision and other applications. This paper presents a new method for affine transformation detection. The state-of-the-art methods are mainly divided into two classes. One class is based on complicated descriptors. But this kind of methods need a lot of time to establish and matching the complicated descriptors. The second class is based on probabilistic model. But these methods can not yield good matching result in some difficult conditions. Our method tries to combine the two kinds of methods together, so as to acquire the accuracy and efficiency at the same time.
Keywords
computer vision; image matching; object detection; probability; transforms; affine transformation detection; computer vision; probabilistic model; robust affine invariant feature matching; Accuracy; Computer vision; Detectors; Histograms; Probabilistic logic; Robustness; Training; Affine Invariance; Feature Matching; Learning-Based;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Applications and Workshops (ICMLA), 2011 10th International Conference on
Conference_Location
Honolulu, HI
Print_ISBN
978-1-4577-2134-2
Type
conf
DOI
10.1109/ICMLA.2011.21
Filename
6146961
Link To Document