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» Novel image feature alphabets for object recognition
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ICIAP
2007
ACM
14 years 7 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
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...
ICCV
2007
IEEE
14 years 9 months ago
How Good are Local Features for Classes of Geometric Objects
Recent work in object categorization often uses local image descriptors such as SIFT to learn and detect object categories. Such descriptors explicitly code local appearance and h...
Michael Stark, Bernt Schiele
AMFG
2007
IEEE
315views Biometrics» more  AMFG 2007»
14 years 1 months ago
Structured Ordinal Features for Appearance-Based Object Representation
In this paper, we propose a novel appearance-based representation, called Structured Ordinal Feature (SOF). SOF is a binary string encoded by combining eight ordinal blocks in a ci...
ShengCai Liao, Zhen Lei, Stan Z. Li, Xiaotong Yuan...
ICCV
2009
IEEE
1821views Computer Vision» more  ICCV 2009»
15 years 9 days ago
Feature Correspondence and Deformable Object Matching via Agglomerative Correspondence Clustering
We present an efficient method for feature correspondence and object-based image matching, which exploits both photometric similarity and pairwise geometric consistency from local ...
Minsu Cho (Seoul National University), Jungmin Lee...