LIT: A System and Benchmark for Light Understanding

Tsesmelis, Theodore; Hasan, Irtiza; Cristani, Marco; Bue, Alessio Del; Galasso, Fabio

doi:10.1109/iccvw.2017.348

Cited by 2 publications

(1 citation statement)

References 22 publications

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“…luminaries) in the room. Then we select a subset of images with the LIT method [37] for which a single light source only is active. We use such images to estimate the pixel-wise albedo ρ using a first-order spherical harmonics model [6] with known surface normals obtained from the previous surface reconstruction step.…”

Section: Camera-aided 3d and Reflectance Modellingmentioning

confidence: 99%

RGBD2lux: Dense Light Intensity Estimation With an RGBD Sensor

Tsesmelis¹,

Hasan²,

Cristani³

et al. 2019

2019 IEEE Winter Conference on Applications of Computer Vision (WACV)

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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 propose 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 lightplanning 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 RGBD input.

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Section: Camera-aided 3d and Reflectance Modellingmentioning

confidence: 99%

RGBD2lux: Dense Light Intensity Estimation With an RGBD Sensor

Tsesmelis¹,

Hasan²,

Cristani³

et al. 2019

2019 IEEE Winter Conference on Applications of Computer Vision (WACV)

Self Cite

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An integrated light management system with real-time light measurement and human perception

Tsesmelis

Hasan

Cristani

et al. 2020

Lighting Research & Technology

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Illumination is important for well-being, productivity and safety across several environments, including offices, retail shops and industrial warehouses. Current techniques for setting up lighting require extensive and expert support and need to be repeated if the scene changes. Here we propose the first fully automated light management system which measures lighting in real-time, leveraging an RGBD sensor and a radiosity-based light propagation model. Thanks to the integration of light distribution and perception curves into the radiosity, we outperform a commercial software (Relux) on a newly introduced dataset. Furthermore, our proposed light management system is the first to estimate both the presence and the attention of the people in the environment, as well as their light perception. Our new light management system adapts lighting to the scene and human activity and it is capable of energy savings of up to 66%, as we experimentally quantify, without compromising the lighting quality.

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LIT: A System and Benchmark for Light Understanding

Cited by 2 publications

References 22 publications

RGBD2lux: Dense Light Intensity Estimation With an RGBD Sensor

RGBD2lux: Dense Light Intensity Estimation With an RGBD Sensor

An integrated light management system with real-time light measurement and human perception

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