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dc.contributor.authorMurmann, Lukas
dc.contributor.authorDavis, Abe
dc.contributor.authorKautz, Jan
dc.contributor.authorDurand, Frédo
dc.contributor.authorDavis, Abe
dc.date.accessioned2021-01-13T22:13:12Z
dc.date.available2021-01-13T22:13:12Z
dc.date.issued2016-11
dc.identifier.issn0730-0301
dc.identifier.issn1557-7368
dc.identifier.urihttps://hdl.handle.net/1721.1/129416
dc.description.abstractPortraits 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.en_US
dc.language.isoen
dc.publisherAssociation for Computing Machinery (ACM)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1145/2980179.2980219en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceACMen_US
dc.titleComputational bounce flash for indoor portraitsen_US
dc.typeArticleen_US
dc.identifier.citationMurmann, Lukas et al. "Computational bounce flash for indoor portraits." ACM Transactions on Graphics 35, 6 (November 2016): 190 © 2016 The Authorsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.relation.journalACM Transactions on Graphicsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2019-05-29T12:45:01Z
dspace.date.submission2019-05-29T12:45:08Z
mit.journal.volume35en_US
mit.journal.issue6en_US
mit.metadata.statusComplete


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