Shape-based image segmentation through photometric stereo
Entidad
UAM. Departamento de Tecnología Electrónica y de las ComunicacionesEditor
Elsevier B. V.Fecha de edición
2011-01Cita
10.1016/j.cviu.2010.09.009
Computer Vision and Image Understanding 115.1 (2011): 91-104
ISSN
1077-3142 (print); 1090-235X (online)DOI
10.1016/j.cviu.2010.09.009Financiado por
This work has partially been supported by the Spanish Government under project DPI2007-66556-C03-03, by the Commissioner for Universities and Research of the Department of Innovation, Universities and Companies of the Catalonian Government and by the European Social Fund.Versión del editor
http://dx.doi.org/10.1016/j.cviu.2010.09.009Materias
3D surface normals; Graph-based image segmentation; Photometric stereo; Informática; TelecomunicacionesNota
This is the author’s version of a work that was accepted for publication in Computer Vision and Image Understanding. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Vision and Image Understanding, 115, 1 (2011): 91-104 DOI: 10.1016/j.cviu.2010.09.009Derechos
© 2011 Elsevier B.V. All rights reservedEsta obra está bajo una licencia de Creative Commons Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional.
Resumen
This paper describes a new algorithm for segmenting 2D images by taking into account 3D shape information. The proposed approach consists of two stages. In the first stage, the 3D surface normals of the objects present in the scene are estimated through robust photometric stereo. Then, the image is segmented by grouping its pixels according to their estimated normals through graph-based clustering. One of the advantages of the proposed approach is that, although the segmentation is based on the 3D shape of the objects, the photometric stereo stage used to estimate the 3D normals only requires a set of 2D images. This paper provides an extensive validation of the proposed approach by comparing it with several image segmentation algorithms. Particularly, it is compared with both appearance-based image segmentation algorithms and shape-based ones. Experimental results confirm that the latter are more suitable when the objective is to segment the objects or surfaces present in the scene. Moreover, results show that the proposed approach yields the best image segmentation in most of the cases.
Lista de ficheros
Google Scholar:Juliá, Carme
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Moreno, Rodrigo
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Puig, Domenec
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García García, Miguel Ángel
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