Reflectance and Shape Estimation with a Light Field Camera Under Natural Illumination

Thanh Trung Ngo, Hajime Nagahara, Ko Nishino, Rin ichiro Taniguchi, Yasushi Yagi

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Reflectance and shape are two important components in visually perceiving the real world. Inferring the reflectance and shape of an object through cameras is a fundamental research topic in the field of computer vision. While three-dimensional shape recovery is pervasive with varieties of approaches and practical applications, reflectance recovery has only emerged recently. Reflectance recovery is a challenging task that is usually conducted in controlled environments, such as a laboratory environment with a special apparatus. However, it is desirable that the reflectance be recovered in the field with a handy camera so that reflectance can be jointly recovered with the shape. To that end, we present a solution that simultaneously recovers the reflectance and shape (i.e., dense depth and normal maps) of an object under natural illumination with commercially available handy cameras. We employ a light field camera to capture one light field image of the object, and a 360-degree camera to capture the illumination. The proposed method provides positive results in both simulation and real-world experiments.

Original languageEnglish
Pages (from-to)1707-1722
Number of pages16
JournalInternational Journal of Computer Vision
Volume127
Issue number11-12
DOIs
Publication statusPublished - Dec 1 2019

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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