Causes and corrections for bimodal multi-path scanning with structured light

Yu Zhang, Daniel L. Lau, Ying Yu

Producción científica: Conference contributionrevisión exhaustiva

18 Citas (Scopus)

Resumen

Structured light illumination is an active 3D scanning technique based on projecting/capturing a set of striped patterns and measuring the warping of the patterns as they reflect off a target object's surface. As designed, each pixel in the camera sees exactly one pixel from the projector; however, there are multi-path situations when the scanned surface has a complicated geometry with step edges and other discontinuities in depth or where the target surface has specularities that reflect light away from the camera. These situations are generally referred to multi-path where a camera pixel sees light from multiple projector positions. In the case of bimodal multi-path, the camera pixel receives light from exactly two positions which occurs along a step edge where the edge slices through a pixel so that the pixel sees both a foreground and background surface. In this paper, we present a general mathematical model to address the bimodal multi-path issue in a phase-measuring-profilometry scanner to measure the constructive and destructive interference between the two light paths, and by taking advantage of this interesting cue, separate the paths and make two decoupled phase measurements. We validate our algorithm with a number of challenging real-world scenarios, outperforming the state-of-the-art method.

Idioma originalEnglish
Título de la publicación alojadaProceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019
Páginas4426-4434
Número de páginas9
ISBN (versión digital)9781728132938
DOI
EstadoPublished - jun 2019
Evento32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019 - Long Beach, United States
Duración: jun 16 2019jun 20 2019

Serie de la publicación

NombreProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volumen2019-June
ISSN (versión impresa)1063-6919

Conference

Conference32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019
País/TerritorioUnited States
CiudadLong Beach
Período6/16/196/20/19

Nota bibliográfica

Publisher Copyright:
© 2019 IEEE.

Financiación

National Science Foundation under contract No. 1539157

FinanciadoresNúmero del financiador
National Science Foundation Arctic Social Science Program1539157
National Science Foundation Arctic Social Science Program

    ASJC Scopus subject areas

    • Software
    • Computer Vision and Pattern Recognition

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