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Object recognition and detection by a combination of support vector machine and rotation invariant phase only correlation

Nakajima, C; Itoh, N; Pontil, M; Poggio, T; (2000) Object recognition and detection by a combination of support vector machine and rotation invariant phase only correlation. In: Sanfeliu, A and Villanueva, JJ and Vanrell, M and Alquezar, R and Crowley, J and Shirai, Y, (eds.) 15TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 4, PROCEEDINGS. (pp. 787 - 790). IEEE COMPUTER SOC

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Abstract

This paper proposes an object recognition and detection method by a combination of Support Vector Machine Classifier (SVM) and Rotation Invariant Phase Only Correlation (RIPOC). SVM is a learning technique that is well founded in statistical learning theory. RIPOC is a position and rotation invariant pattern matching technique. We combined these two techniques to develop an augmented reality system. This system can recognize and detect objects from image sequences without special image marks or sensors and show information about the objects through a head-mounded display. Performance is real time.

Type:Proceedings paper
Title:Object recognition and detection by a combination of support vector machine and rotation invariant phase only correlation
Event:15th International Conference on Pattern Recognition (ICPR-2000)
Location:BARCELONA, SPAIN
Dates:2000-09-03 - 2000-09-07
ISBN:0-7695-0751-4
UCL classification:UCL > School of BEAMS > Faculty of Engineering Science > Computer Science

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