NDLI: A Model-based Approach for Rigid Object Recognition

Content Provider	IEEE Xplore Digital Library
Author	Chee Boon Chong Tele Tan Fee Lee Lim
Copyright Year	2006
Description	Author affiliation: Dept. of Comput., Curtin Univ. of Technol., Perth, WA (Chee Boon Chong; Tele Tan; Fee Lee Lim)
Abstract	Most object recognition systems require large databases of real images for classifier training. To collect real images for this purpose is a difficult and expensive process. This paper introduces a unified framework based on the creation and use of synthetic images for training various classifiers to achieve recognition of real-world objects. A 3D model of the object (i.e. trolley in this case) is constructed from a minimum of two photographs. The constructed 3D model is used to automatically generate the relevant synthetic images that are subsequently used to train the Adaboost and support vector machine-based recognition systems. Experimental results obtained are very encouraging suggesting that synthetically generated images generated by our approach can augment the real training samples used in current recognition systems
Sponsorship	IEEE CPS
Starting Page	116
Ending Page	120
File Size	1440451
Page Count	5
File Format	PDF
ISBN	0769525210
ISSN	10514651
DOI	10.1109/ICPR.2006.103
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Object recognition Support vector machines Image recognition Support vector machine classification Computer vision Training data Image databases Image generation Error analysis Testing
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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