RGBD2lux: Dense light intensity estimation with an RGBD sensor
September 20, 2018 Β· Declared Dead Β· π IEEE Workshop/Winter Conference on Applications of Computer Vision
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Authors
Theodore Tsesmelis, Irtiza Hasan, Marco Cristani, Fabio Galasso, Alessio Del Bue
arXiv ID
1809.07558
Category
cs.CV: Computer Vision
Citations
12
Venue
IEEE Workshop/Winter Conference on Applications of Computer Vision
Last Checked
3 months ago
Abstract
Lighting design and modelling or industrial applications like luminaire planning and commissioning rely heavily on time consuming manual measurements or on physically coherent computational simulations. Regarding the latter,standard approaches are based on CAD modeling simulations and offline rendering, with long processing times and therefore inflexible workflows. Thus, in this paper we pro-pose a computer vision based system to measure lighting with just a single RGBD camera. The proposed method uses both depth data and images from the sensor to provide a dense measure of light intensity in the field of view of the camera. We evaluate our system on novel ground truth data and compare it to state-of-the-art commercial light-planning software. Our system provides improved performance, while being completely automated, given that the CAD model is extracted from the depth and the albedo estimated with the support of RGB images. To the best of our knowledge, this is the first automatic framework for the estimation of lighting in general indoor scenarios from RGBDinput.
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