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 original | English |
|---|---|
| Título de la publicación alojada | Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019 |
| Páginas | 4426-4434 |
| Número de páginas | 9 |
| ISBN (versión digital) | 9781728132938 |
| DOI | |
| Estado | Published - jun 2019 |
| Evento | 32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019 - Long Beach, United States Duración: jun 16 2019 → jun 20 2019 |
Serie de la publicación
| Nombre | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
|---|---|
| Volumen | 2019-June |
| ISSN (versión impresa) | 1063-6919 |
Conference
| Conference | 32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019 |
|---|---|
| País/Territorio | United States |
| Ciudad | Long Beach |
| Período | 6/16/19 → 6/20/19 |
Nota bibliográfica
Publisher Copyright:© 2019 IEEE.
Financiación
National Science Foundation under contract No. 1539157
| Financiadores | Número del financiador |
|---|---|
| National Science Foundation Arctic Social Science Program | 1539157 |
| National Science Foundation Arctic Social Science Program |
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition