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Proceedings Paper

Contour-based object orientation estimation
Author(s): Boris Alpatov; Pavel Babayan
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Paper Abstract

Real-time object orientation estimation is an actual problem of computer vision nowadays. In this paper we propose an approach to estimate an orientation of objects lacking axial symmetry. Proposed algorithm is intended to estimate orientation of a specific known 3D object, so 3D model is required for learning. The proposed orientation estimation algorithm consists of 2 stages: learning and estimation. Learning stage is devoted to the exploring of studied object. Using 3D model we can gather set of training images by capturing 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. It minimizes the training image set. Gathered training image set is used for calculating descriptors, which will be used in the estimation stage of the algorithm. The estimation stage is focusing on matching process between an observed image descriptor and the training image descriptors. The experimental research was performed using a set of images of Airbus A380. The proposed orientation estimation algorithm showed good accuracy (mean error value less than 6°) in all case studies. The real-time performance of the algorithm was also demonstrated.

Paper Details

Date Published: 29 April 2016
PDF: 6 pages
Proc. SPIE 9897, Real-Time Image and Video Processing 2016, 98970H (29 April 2016); doi: 10.1117/12.2224249
Show Author Affiliations
Boris Alpatov, Ryazan State Radio Engineering Univ. (Russian Federation)
Pavel Babayan, Ryazan State Radio Engineering Univ. (Russian Federation)

Published in SPIE Proceedings Vol. 9897:
Real-Time Image and Video Processing 2016
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)

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