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» On SIFTs and their scales
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ACIVS
2006
Springer
14 years 1 months ago
Context-Based Scene Recognition Using Bayesian Networks with Scale-Invariant Feature Transform
Scene understanding is an important problem in intelligent robotics. Since visual information is uncertain due to several reasons, we need a novel method that has robustness to the...
Seung-Bin Im, Sung-Bae Cho
ACCV
2009
Springer
14 years 1 months ago
A Harris-Like Scale Invariant Feature Detector
Image feature detection is a fundamental issue in computer vision. SIFT[1] and SURF[2] are very effective in scale-space feature detection, but their stabilities are not good enou...
Yinan Yu, Kaiqi Huang, Tieniu Tan
ISBI
2007
IEEE
14 years 4 months ago
N-Sift: N-Dimensional Scale Invariant Feature Transform for Matching Medical Images
We present a fully automated multimodal medical image matching technique. Our method extends the concepts used in the computer vision SIFT technique for extracting and matching di...
Warren Cheung, Ghassan Hamarneh
MM
2010
ACM
462views Multimedia» more  MM 2010»
13 years 10 months ago
KPB-SIFT: a compact local feature descriptor
Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and object recognition. However, such descriptors are typically of ...
Gangqiang Zhao, Ling Chen, Gencai Chen, Junsong Yu...
SCIA
2009
Springer
118views Image Analysis» more  SCIA 2009»
14 years 2 months ago
Grouping of Semantically Similar Image Positions
Features from the Scale Invariant Feature Transformation (SIFT) are widely used for matching between spatially or temporally displaced images. Recently a topology on the SIFT featu...
Lutz Priese, Frank Schmitt, Nils Hering