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20 February 2012 An evaluation of different setups for simulating lighting characteristics
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Proceedings Volume 8291, Human Vision and Electronic Imaging XVII; 82911M (2012)
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States
The advance of technology continuously enables new luminaire designs and concepts. Evaluating such designs has traditionally been done using actual prototypes, in a real environment. The iterations needed to build, verify, and improve luminaire designs incur substantial costs and slow down the design process. A more attractive way is to evaluate designs using simulations, as they can be made cheaper and quicker for a wider variety of prototypes. However, the value of such simulations is determined by how closely they predict the outcome of actual perception experiments. In this paper, we discuss an actual perception experiment including several lighting settings in a normal office environment. The same office environment also has been modeled using different software tools, and photo-realistic renderings have been created of these models. These renderings were subsequently processed using various tonemapping operators in preparation for display. The total imaging chain can be considered a simulation setup, and we have executed several perception experiments on different setups. Our real interest is in finding which imaging chain gives us the best result, or in other words, which of them yields the closest match between virtual and real experiment. To answer this question, first of all an answer has to be found to the question, "which simulation setup matches the real world best?" As there is no unique, widely accepted measure to describe the performance of a certain setup, we consider a number of options and discuss the reasoning behind them along with their advantages and disadvantages.
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Bart Salters, Michael Murdoch, Dragan Sekulovksi, Shih-Han Chen, and Pieter Seuntiens "An evaluation of different setups for simulating lighting characteristics", Proc. SPIE 8291, Human Vision and Electronic Imaging XVII, 82911M (20 February 2012);


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