Normal Integration: A Survey

Abstract : The need for efficient normal integration methods is driven by several computer vision tasks such as shape-from-shading, photometric stereo, deflectometry, etc. In the first part of this survey, we select the most important properties that one may expect from a normal integration method, based on a thorough study of two pioneering works by Horn and Brooks [28] and by Frankot and Chellappa [19]. Apart from accuracy, an integration method should at least be fast and robust to a noisy normal field. In addition, it should be able to handle several types of boundary condition, including the case of a free boundary, and a reconstruction domain of any shape i.e., which is not necessarily rectangular. It is also much appreciated that a minimum number of parameters have to be tuned, or even no parameter at all. Finally, it should preserve the depth discontinuities. In the second part of this survey, we review most of the existing methods in view of this analysis, and conclude that none of them satisfies all of the required properties. This work is complemented by a companion paper entitled Variational Methods for Normal Integration, in which we focus on the problem of normal integration in the presence of depth discontinuities, a problem which occurs as soon as there are occlusions.
Liste complète des métadonnées

Littérature citée [68 références]  Voir  Masquer  Télécharger

https://hal.archives-ouvertes.fr/hal-01334349
Contributeur : Yvain Quéau <>
Soumis le : mercredi 25 octobre 2017 - 09:57:32
Dernière modification le : jeudi 26 octobre 2017 - 01:07:51

Fichier

article_1.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01334349, version 4

Collections

Citation

Yvain Queau, Jean-Denis Durou, Jean-François Aujol. Normal Integration: A Survey. 2016. 〈hal-01334349v4〉

Partager

Métriques

Consultations de la notice

17

Téléchargements de fichiers

11