Lighting design and modelling (the efficient and aesthetic placement of luminaires in a virtual or real scene) or industrial applications like luminaire planning and commissioning (the luminaire's installation and evaluation process along to the scene's geometry and structure) rely heavily on high realism and physically correct simulations. The current typical approaches are based only on CAD modeling simulations and offline rendering, with long processing times and therefore inflexible workflows. In this thesis we examine whether different camera-aided light modeling and numerical optimization approaches could be used to accurately understand, model and measure the light distribution in real life scenarios within real world environments. We show that factorization techniques could play a semantic role for light decomposition and light source identification, while we contribute a novel benchmark dataset and metrics for it. Thereafter we adapt a well known global illumination model (i.e. radiosity) and we extend it so that to overcome some of its basic limitations related to the assumption of point based only light sources or the adaption of only isotropic light perception sensors. We show that this extended radiosity numerical model can challenge the state-of-the-art in obtaining accurate dense spatial light measurements over time and in different scenarios. Finally we combine the latter model with human-centric sensing information and present how this could be beneficial for smart lighting applications related to quality lighting and power efficiency. Thus, with this work we contribute by setting the baselines for using an RGBD camera input as the only requirement to light modeling methods for light estimation in real life scenarios, and open a new applicability where the illumination modeling can be turned into an interactive process, allowing for real-time modifications and immediate feedback on the spatial illumination of a scene over time towards quality lighting and energy efficient solutions.
Measuring and understanding light in real life scenarios
TSESMELIS, THEODOROSWriting – Original Draft Preparation
2019-01-01
Abstract
Lighting design and modelling (the efficient and aesthetic placement of luminaires in a virtual or real scene) or industrial applications like luminaire planning and commissioning (the luminaire's installation and evaluation process along to the scene's geometry and structure) rely heavily on high realism and physically correct simulations. The current typical approaches are based only on CAD modeling simulations and offline rendering, with long processing times and therefore inflexible workflows. In this thesis we examine whether different camera-aided light modeling and numerical optimization approaches could be used to accurately understand, model and measure the light distribution in real life scenarios within real world environments. We show that factorization techniques could play a semantic role for light decomposition and light source identification, while we contribute a novel benchmark dataset and metrics for it. Thereafter we adapt a well known global illumination model (i.e. radiosity) and we extend it so that to overcome some of its basic limitations related to the assumption of point based only light sources or the adaption of only isotropic light perception sensors. We show that this extended radiosity numerical model can challenge the state-of-the-art in obtaining accurate dense spatial light measurements over time and in different scenarios. Finally we combine the latter model with human-centric sensing information and present how this could be beneficial for smart lighting applications related to quality lighting and power efficiency. Thus, with this work we contribute by setting the baselines for using an RGBD camera input as the only requirement to light modeling methods for light estimation in real life scenarios, and open a new applicability where the illumination modeling can be turned into an interactive process, allowing for real-time modifications and immediate feedback on the spatial illumination of a scene over time towards quality lighting and energy efficient solutions.File | Dimensione | Formato | |
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Measuring_and_understanding_light_in_real_life_scenarios(doctoral_thesis)_.pdf
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Descrizione: Doctoral thesis conducted within the framework of the SceneUnderLight project. The focus of this research was to encompass computer vision and smart lighting for a new generation of smart lighting management systems.
Tipologia:
Tesi di dottorato
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Dominio pubblico
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6.43 MB
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