Normal Integration: A Survey
QUÉAU, Yvain
Technische Universität Munchen - Technical University Munich - Université Technique de Munich [TUM]
Technische Universität Munchen - Technical University Munich - Université Technique de Munich [TUM]
AUJOL, Jean-François
Institut de Mathématiques de Bordeaux [IMB]
Institut universitaire de France [IUF]
Institut de Mathématiques de Bordeaux [IMB]
Institut universitaire de France [IUF]
QUÉAU, Yvain
Technische Universität Munchen - Technical University Munich - Université Technique de Munich [TUM]
Technische Universität Munchen - Technical University Munich - Université Technique de Munich [TUM]
AUJOL, Jean-François
Institut de Mathématiques de Bordeaux [IMB]
Institut universitaire de France [IUF]
< Leer menos
Institut de Mathématiques de Bordeaux [IMB]
Institut universitaire de France [IUF]
Idioma
en
Article de revue
Este ítem está publicado en
Journal of Mathematical Imaging and Vision. 2018-05, vol. 60, n° 4, p. 576-593
Springer Verlag
Resumen en inglés
The need for efficient normal integration methods is driven by several computer vision tasks such as shape-from-shading, photometric stereo, deflectometry. In the first part of this survey, we select the most important ...Leer más >
The need for efficient normal integration methods is driven by several computer vision tasks such as shape-from-shading, photometric stereo, deflectometry. 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 rooks (Comput Vis Graph Image Process 33(2): 174-208, 1986) and Frankot and Chellappa (IEEE Trans Pattern Anal Mach Intell 10(4): 439-451, 1988). 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.< Leer menos
Palabras clave en inglés
3D-reconstruction
integration
normal field
gradient field
Orígen
Importado de HalCentros de investigación