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» Maximally Stable Local Description for Scale Selection
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IROS
2006
IEEE
128views Robotics» more  IROS 2006»
14 years 1 months ago
Improving Data Association in Vision-based SLAM
— This paper presents an approach to vision-based simultaneous localization and mapping (SLAM). Our approach uses the scale invariant feature transform (SIFT) as features and app...
Arturo Gil, Óscar Reinoso, Óscar Mar...
ICPR
2008
IEEE
14 years 9 months ago
Feature selection for real-time image matching systems
This paper proposes a general feature selection approach for real-time image matching systems. To demonstrate the idea's effectiveness, we focus on the issue of rotational in...
Quan Wang, Suya You
BMCV
2000
Springer
14 years 1 days ago
Towards a Computational Model for Object Recognition in IT Cortex
First IEEE International Workshop on Biologically Motivated Computer Vision, Seoul, Korea (May 2000). There is considerable evidence that object recognition in primates is based o...
David G. Lowe
TIP
2008
142views more  TIP 2008»
13 years 7 months ago
Image Feature Localization by Multiple Hypothesis Testing of Gabor Features
Several novel and particularly successful object and object category detection and recognition methods based on image features, local descriptions of object appearance, have recent...
Jarmo Ilonen, Joni-Kristian Kamarainen, Pekka Paal...
PAKDD
1999
ACM
113views Data Mining» more  PAKDD 1999»
13 years 12 months ago
Characterization of Default Knowledge in Ripple Down Rules Method
Abstract. \Ripple Down Rules (RDR)" Method is one of the promising approaches to directly acquire and encode knowledge from human experts. It requires data to be supplied incr...
Takuya Wada, Tadashi Horiuchi, Hiroshi Motoda, Tak...