Since 15 March 2021, this page is not updated anymore and serves purely as an archive of previous activities. The webpage of Christian Sandor’s new team is now located at: https://ar-lab.org.

Alvaro Casinelli’s new team webpage will be announced soon. In the meantime, you can find out more about his work at https://www.alvarocassinelli.com.

Robust Reflectance Estimation for Projection-Based Appearance Control in a Dynamic Light Environment

Abstract

We present a novel method that robustly estimates the reflectance, even in an environment with dynamically changing light. To control the appearance of an object by using a projector–camera system, an appropriate estimate of the object’s reflectance is vital to the creation of an appropriate projection image. Most conventional estimation methods assume static light conditions; however, in practice, the appearance is affected by both the reflectance and environmental light. In an environment with dynamically changing light, conventional reflectance estimation methods require calibration every time the conditions change. In contrast, our method requires no additional calibration because it simultaneously estimates both the reflectance and environmental light. Our method is based on the concept of creating two different light conditions by switching the projection at a rate higher than that perceived by the human eye and captures the images of a target object separately under each condition. The reflectance and environmental light are then simultaneously estimated by using the pair of images acquired under these two conditions. We implemented a projector–camera system that switches the projection on and off at 120 Hz. Experiments confirm the robustness of our method when changing the environmental light. Further, our method can robustly estimate the reflectance under practical indoor lighting conditions.

Publication
IEEE Transactions on Visualization and Computer Graphics