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

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.

Publication
International Journal of Computer Vision
Hajime Nagahara
Hajime Nagahara
Professor

He is working on computer vision and pattern recognition. His main research interests lie in image/video recognition and understanding, as well as applications of natural language processing techniques.