PROCEEDINGS OF THE ITE WINTER ANNUAL CONVENTION
Online ISSN : 2424-2306
Print ISSN : 1343-4357
ISSN-L : 1343-4357
2012
Session ID : 12-14
Conference information

Name : 2012 ITE Winter Annual Convention

Location : [in Japanese]

Date : December 18, 2012 - December 19, 2012

12-14 A Viewpoint Classification Method for 3D Object Detection
Tatsuya Kobayashi, Haruhisa Kato, Akio Yoneyama
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Abstract
We present a novel viewpoint classification method for 3D objects. The proposed method cooperates with a 2D-3D matching method and estimate the viewpoint accurately even if the target is seen from any possible angles. Our results showed that the proposed method improves classification accuracy by about 50 percentage points.
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© 2012 The Institute of Image Information and Television Engineers
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