Object recognition using relative-chord context
| Autor: | Chai Hua, Ronsin Joseph, Yang Ming-qiang, Kpalma Kidiyo |
|---|---|
| Přispěvatelé: | School of Information Science and Engineering (ISE), Shandong University, Institut d'Electronique et de Télécommunications de Rennes (IETR), Centre National de la Recherche Scientifique (CNRS)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: |
relative-chord
correlation statistics business.industry 3D single-object recognition 020208 electrical & electronic engineering Feature extraction Cognitive neuroscience of visual object recognition Columbia university Pattern recognition 02 engineering and technology affine transformation object recognition [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Histogram 0202 electrical engineering electronic engineering information engineering Chord (music) 020201 artificial intelligence & image processing Computer vision Affine transformation Artificial intelligence business [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing Mathematics |
| Zdroj: | International Conference on Consumer Electronics, Communications and Networks International Conference on Consumer Electronics, Communications and Networks (CECNet) International Conference on Consumer Electronics, Communications and Networks (CECNet), Apr 2011, Jinan, China. pp.515-518, ⟨10.1109/CECNET.2011.5768917⟩ |
| DOI: | 10.1109/CECNET.2011.5768917⟩ |
| Popis: | International audience; In this paper the relative-chord context is proposed for shape description in object recognition. The relative-chord is introduced to obtain the affine-invariant feature. The intervals of parallel chords are normalized by vertical direction-chord. Experimental result based on the Columbia University Coil-100 3D database demonstrates the feasibility of the relative-chord context methodology and also highlights its invariance to affine transforms. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|