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GECCO
2009
Springer
258views Optimization» more  GECCO 2009»
13 years 10 months ago
Evolutionary learning of local descriptor operators for object recognition
Nowadays, object recognition is widely studied under the paradigm of matching local features. This work describes a genetic programming methodology that synthesizes mathematical e...
Cynthia B. Pérez, Gustavo Olague
ICIAP
2007
ACM
14 years 5 months ago
A Method for Blur and Similarity Transform Invariant Object Recognition
In this paper, we propose novel blur and similarity transform (i.e. rotation, scaling and translation) invariant features for the recognition of objects in images. The features ar...
Janne Heikkilä, Ville Ojansivu
ICCV
2011
IEEE
12 years 5 months ago
Local Intensity Order Pattern for Feature Description
This paper presents a novel method for feature description based on intensity order. Specifically, a Local Intensity Order Pattern(LIOP) is proposed to encode the local ordinal i...
Zhenhua Wang, Bin Fan, Fuchao Wu
ECCV
2010
Springer
13 years 11 months ago
Rotation invariant non-rigid shape matching in cluttered scenes
Abstract. This paper presents a novel and efficient method for locating deformable shapes in cluttered scenes. The shapes to be detected may undergo arbitrary translational and rot...
TSP
2008
187views more  TSP 2008»
13 years 5 months ago
Invariant Description and Retrieval of Planar Shapes Using Radon Composite Features
This paper proposes a novel feature-based invariant descriptor termed Radon composite features (RCFs) for planar shapes. Instead of analyzing shapes directly in the spatial domain,...
Yun Wen Chen, Yan Qiu Chen