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Computational bounce flash for indoor portraits

Author(s)
Murmann, Lukas; Davis, Abe; Kautz, Jan; Durand, Frédo; Davis, Abe
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Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/
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Abstract
Portraits taken with direct flash look harsh and unflattering because the light source comes from a small set of angles very close to the camera. Advanced photographers address this problem by using bounce flash, a technique where the flash is directed towards other surfaces in the room, creating a larger, virtual light source that can be cast from different directions to provide better shading variation for 3D modeling. However, finding the right direction to point a bounce flash requires skill and careful consideration of the available surfaces and subject configuration. Inspired by the impact of automation for exposure, focus and flash metering, we automate control of the flash direction for bounce illumination. We first identify criteria for evaluating flash directions, based on established photography literature, and relate these criteria to the color and geometry of a scene. We augment a camera with servomotors to rotate the flash head, and additional sensors (a fisheye and 3D sensors) to gather information about potential bounce surfaces. We present a simple numerical optimization criterion that finds directions for the flash that consistently yield compelling illumination and demonstrate the effectiveness of our various criteria in common photographic configurations.
Date issued
2016-11
URI
https://hdl.handle.net/1721.1/129416
Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Journal
ACM Transactions on Graphics
Publisher
Association for Computing Machinery (ACM)
Citation
Murmann, Lukas et al. "Computational bounce flash for indoor portraits." ACM Transactions on Graphics 35, 6 (November 2016): 190 © 2016 The Authors
Version: Final published version
ISSN
0730-0301
1557-7368

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