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Authors: Yanan Miao 1 ; Huan Ma 1 ; Xiaoming Tao 2 and Jia Cui 1

Affiliations: 1 National Computer Network Emergency Response Technical Team/Coordination Center of China, China ; 2 Tsinghua University, China

ISBN: 978-989-758-276-9

Keyword(s): Landmarks Localization, 3D Shape Estimation, Pose Estimation, Cascaded Regression.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Geometry and Modeling ; Image-Based Modeling ; Pattern Recognition ; Regression ; Shape Representation ; Software Engineering ; Theory and Methods

Abstract: Previous works on reconstruction of a three-dimensional (3D) point shape model commonly use a two-step framework. Precisely localizing a series of feature points in an image is performed on the first step. Then the second procedure attempts to fit the 3D data to the observations to get the real 3D shape. Such an approach has high time consumption, and easily gets stuck into local minimum. To address this problem, we propose a method to jointly estimate the global 3D geometric structure of car and localize 2D landmarks from a single viewpoint image. First, we parametrizing the 3D shape by the coefficients of the linear combination of a set of predefined shape bases. Second, we adopt a cascaded regression framework to regress the global shape encoded by the prior bases, by jointly minimizing the appearance and shape fitting differences under a weak projection camera model. The position fitting item can help cope with the description ambiguity of local appearance, and provide mo re information for 3D reconstruction. Experimental results on a multi-view car dataset demonstrate favourable improvements on pose estimation and shape prediction, compared with some previous methods. (More)

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Paper citation in several formats:
Miao, Y.; Ma, H.; Cui, J. and Tao, X. (2018). Joint Monocular 3D Car Shape Estimation and Landmark Localization via Cascaded Regression.In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-276-9, pages 222-232. DOI: 10.5220/0006715102220232

@conference{icpram18,
author={Yanan Miao. and Huan Ma. and Jia Cui. and Xiaoming Tao.},
title={Joint Monocular 3D Car Shape Estimation and Landmark Localization via Cascaded Regression},
booktitle={Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2018},
pages={222-232},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006715102220232},
isbn={978-989-758-276-9},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Joint Monocular 3D Car Shape Estimation and Landmark Localization via Cascaded Regression
SN - 978-989-758-276-9
AU - Miao, Y.
AU - Ma, H.
AU - Cui, J.
AU - Tao, X.
PY - 2018
SP - 222
EP - 232
DO - 10.5220/0006715102220232

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