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Estimation of position and intensity of dynamic light sources using cast shadows on textured real surfaces

Salma Jiddi 1, 2 Philippe Robert 1 Eric Marchand 2
2 RAINBOW - Sensor-based and interactive robotics
Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : In this paper, we consider the problem of estimating the 3D position and intensity of multiple light sources without using any light probe or user interaction. The proposed approach is twofold and relies on RGB-D data acquired with a low cost 3D sensor. First, we separate albedo/texture and illumination using lightness ratios between pairs of points with the same reflectance property but subject to different lighting conditions. Our selection algorithm is robust in presence of challenging textured surfaces. Then, estimated illumination ratios are integrated, at each frame, within an iterative process to recover position and intensity of light sources responsible of cast shadows. Estimated lighting characteristics are finally used to achieve realistic Augmented Reality (AR).
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Submitted on : Wednesday, June 13, 2018 - 7:41:23 PM
Last modification on : Friday, July 10, 2020 - 4:20:55 PM
Long-term archiving on: : Monday, September 17, 2018 - 11:31:37 AM

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Salma Jiddi, Philippe Robert, Eric Marchand. Estimation of position and intensity of dynamic light sources using cast shadows on textured real surfaces. ICIP 2018 - 25th IEEE International Conference on Image Processing, Oct 2018, Athens, Greece. pp.1063-1067, ⟨10.1109/ICIP.2018.8451078⟩. ⟨hal-01815195⟩

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