@InProceedings{6952585,
  author = {J. Kronander and J. Dahlin and D. Jönsson and M. Kok and T. B. Schön and J. Unger},
  booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},
  title = {Real-time video based lighting using GPU raytracing},
  year = {2014},
  pages = {1627-1631},
  abstract = {The recent introduction of high dynamic range (HDR) video cameras has enabled the development of image based lighting techniques for rendering virtual objects illuminated with temporally varying real world illumination. A key challenge in this context is that rendering realistic objects illuminated with video environment maps is computationally demanding. In this work, we present a GPU based rendering system based on the NVIDIA OptiX [1] framework, enabling real time raytracing of scenes illuminated with video environment maps. For this purpose, we explore and compare several Monte Carlo sampling approaches, including bidirectional importance sampling, multiple importance sampling and sequential Monte Carlo samplers. While previous work have focused on synthetic data and overly simple environment map sequences, we have collected a set of real world dynamic environment map sequences using a state-of-art HDR video camera for evaluation and comparisons. Based on the result we show that in contrast to CPU renderers, for a GPU implementation multiple importance sampling and bidirectional importance sampling provide better results than sequential Monte Carlo samplers in terms of flexibility, computational efficiency and robustness.},
  keywords = {graphics processing units;lighting;Monte Carlo methods;ray tracing;video cameras;environment map sequences;synthetic data;sequential Monte Carlo samplers;multiple importance sampling;bidirectional importance sampling;NVIDIA OptiX framework;video environment maps;virtual object rendering;image based lighting;video cameras;HDR;high dynamic range;real-time video based lighting;GPU ray tracing;Lighting;Monte Carlo methods;Rendering (computer graphics);Cameras;Probes;Streaming media;Graphics processing units;Image Based Lighting;HDR Video;Video Based Lighting},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569926583.pdf},
}

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B.","Unger, J."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["J."],"propositions":[],"lastnames":["Kronander"],"suffixes":[]},{"firstnames":["J."],"propositions":[],"lastnames":["Dahlin"],"suffixes":[]},{"firstnames":["D."],"propositions":[],"lastnames":["Jönsson"],"suffixes":[]},{"firstnames":["M."],"propositions":[],"lastnames":["Kok"],"suffixes":[]},{"firstnames":["T.","B."],"propositions":[],"lastnames":["Schön"],"suffixes":[]},{"firstnames":["J."],"propositions":[],"lastnames":["Unger"],"suffixes":[]}],"booktitle":"2014 22nd European Signal Processing Conference (EUSIPCO)","title":"Real-time video based lighting using GPU raytracing","year":"2014","pages":"1627-1631","abstract":"The recent introduction of high dynamic range (HDR) video cameras has enabled the development of image based lighting techniques for rendering virtual objects illuminated with temporally varying real world illumination. A key challenge in this context is that rendering realistic objects illuminated with video environment maps is computationally demanding. In this work, we present a GPU based rendering system based on the NVIDIA OptiX [1] framework, enabling real time raytracing of scenes illuminated with video environment maps. For this purpose, we explore and compare several Monte Carlo sampling approaches, including bidirectional importance sampling, multiple importance sampling and sequential Monte Carlo samplers. While previous work have focused on synthetic data and overly simple environment map sequences, we have collected a set of real world dynamic environment map sequences using a state-of-art HDR video camera for evaluation and comparisons. 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Kronander and J. Dahlin and D. Jönsson and M. Kok and T. B. Schön and J. Unger},\n booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},\n title = {Real-time video based lighting using GPU raytracing},\n year = {2014},\n pages = {1627-1631},\n abstract = {The recent introduction of high dynamic range (HDR) video cameras has enabled the development of image based lighting techniques for rendering virtual objects illuminated with temporally varying real world illumination. A key challenge in this context is that rendering realistic objects illuminated with video environment maps is computationally demanding. In this work, we present a GPU based rendering system based on the NVIDIA OptiX [1] framework, enabling real time raytracing of scenes illuminated with video environment maps. 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