Mercer Kernels for Object Recognition with Local Features

2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) ◽

10.1109/cvpr.2005.223 ◽

2005 ◽

Cited By ~ 7

Author(s):

Siwei Lyu

Keyword(s):

Object Recognition ◽

Local Features ◽

Mercer Kernels

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Non-Mercer Kernels for SVM Object Recognition

Procedings of the British Machine Vision Conference 2004 ◽

10.5244/c.18.16 ◽

2004 ◽

Cited By ~ 31

Author(s):

S. Boughorbel ◽

J.P. Tarel ◽

F. Fleuret

Keyword(s):

Object Recognition ◽

Mercer Kernels

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A Novel Local Features Based Salient Object Recognition Algorithm via Hybrid SVM-QPSO Model

Journal of Multimedia ◽

10.4304/jmm.9.8.1032-1039 ◽

2014 ◽

Vol 9 (8) ◽

Cited By ~ 1

Author(s):

Xin Wang ◽

Tianzhong Zhao ◽

Yi Zeng

Keyword(s):

Object Recognition ◽

Local Features ◽

Recognition Algorithm ◽

Salient Object

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Real-time object recognition using local features on a DSP-based embedded system

Journal of Real-Time Image Processing ◽

10.1007/s11554-008-0083-z ◽

2008 ◽

Vol 3 (4) ◽

pp. 233-253 ◽

Cited By ~ 8

Author(s):

Clemens Arth ◽

Horst Bischof

Keyword(s):

Object Recognition ◽

Embedded System ◽

Real Time ◽

Local Features

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Generic object recognition with local features: From bags to subspaces

The 2013 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2013.6706938 ◽

2013 ◽

Cited By ~ 1

Author(s):

Bisser Raytchev ◽

Yuta Kikutsugi ◽

Ryosuke Shigenaka ◽

Toru Tamaki ◽

Kazufumi Kaneda

Keyword(s):

Object Recognition ◽

Local Features

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Boosting colored local features for generic object recognition

Pattern Recognition and Image Analysis ◽

10.1134/s1054661808020193 ◽

2008 ◽

Vol 18 (2) ◽

pp. 323-327 ◽

Cited By ~ 7

Author(s):

D. Hegazy ◽

J. Denzler

Keyword(s):

Object Recognition ◽

Local Features

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Occluded object recognition using extended local features and hashing

Proceedings of IEEE International Conference on Systems, Man and Cybernetics ◽

10.1109/icsmc.1994.400220 ◽

2002 ◽

Author(s):

Joong-Hwan Baek ◽

K.A. Teague

Keyword(s):

Object Recognition ◽

Local Features

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Class-Specific Low-Dimensional Representation of Local Features for Viewpoint Invariant Object Recognition

Computer Vision – ACCV 2010 - Lecture Notes in Computer Science ◽

10.1007/978-3-642-19318-7_20 ◽

2011 ◽

pp. 250-261

Author(s):

Bisser Raytchev ◽

Yuta Kikutsugi ◽

Toru Tamaki ◽

Kazufumi Kaneda

Keyword(s):

Object Recognition ◽

Local Features ◽

Dimensional Representation ◽

Invariant Object Recognition ◽

Low Dimensional

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Object Recognition with Task Relevant Combined Local Features

Lecture Notes in Computer Science - Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues ◽

10.1007/978-3-540-87442-3_36 ◽

2008 ◽

pp. 285-292 ◽

Cited By ~ 1

Author(s):

Wenjun Zhu ◽

Liqing Zhang

Keyword(s):

Object Recognition ◽

Local Features

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A Semi-supervised Learning Approach to Object Recognition with Spatial Integration of Local Features and Segmentation Cues

Toward Category-Level Object Recognition - Lecture Notes in Computer Science ◽

10.1007/11957959_15 ◽

2006 ◽

pp. 277-300 ◽

Cited By ~ 4

Author(s):

Peter Carbonetto ◽

Gyuri Dorkó ◽

Cordelia Schmid ◽

Hendrik Kück ◽

Nando de Freitas

Keyword(s):

Object Recognition ◽

Supervised Learning ◽

Local Features ◽

Learning Approach ◽

Spatial Integration

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The Application Of Local Features In 3-Dimensional Object Recognition

2015 International Conference on Smart and Sustainable City and Big Data (ICSSC) ◽

10.1049/cp.2015.0260 ◽

2015 ◽

Author(s):

Qingtong Xu ◽

Xuandong An ◽

Wanggen Wan ◽

Jing Wang

Keyword(s):

Object Recognition ◽

Local Features ◽

3 Dimensional ◽

Dimensional Object

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