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Parallax photography: creating 3D cinematic effects from stills
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ACM International Conference Proceeding Series; Vol. 324 archive
Proceedings of Graphics Interface 2009 table of contents
Kelowna, British Columbia, Canada
SESSION: Best student papers table of contents
Pages 111-118  
Year of Publication: 2009
ISBN ~ ISSN:0713-5424 , 978-1-56881-470-4
Authors
Ke Colin Zheng  University of Washington
Alex Colburn  University of Washington
Aseem Agarwala  Adobe Systems, Inc.
Maneesh Agrawala  University of California, Berkeley
David Salesin  Adobe Systems, Inc.
Brian Curless  University of Washington
Michael F. Cohen  Microsoft Research
Sponsor
: The Canadian Human-Computer Communications Society / Société Canadienne du Dialogue Humaine Machine (CHCCS/SCDHM)
Publisher
Canadian Information Processing Society  Toronto, Ont., Canada, Canada
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ABSTRACT

We present an approach to convert a small portion of a light field with extracted depth information into a cinematic effect with simulated, smooth camera motion that exhibits a sense of 3D parallax. We develop a taxonomy of the cinematic conventions of these effects, distilled from observations of documentary film footage and organized by the number of subjects of interest in the scene. We present an automatic, content-aware approach to apply these cinematic conventions to an input light field. A face detector identifies subjects of interest. We then optimize for a camera path that conforms to a cinematic convention, maximizes apparent parallax, and avoids missing information in the input. We describe a GPU-accelerated, temporally coherent rendering algorithm that allows users to create more complex camera moves interactively, while experimenting with effects such as focal length, depth of field, and selective, depth-based desaturation or brightening. We evaluate and demonstrate our approach on a wide variety of scenes and present a user study that compares our 3D cinematic effects to their 2D counterparts.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
Ke Colin Zheng: colleagues
Alex Colburn: colleagues
Aseem Agarwala: colleagues
Maneesh Agrawala: colleagues
David Salesin: colleagues
Brian Curless: colleagues
Michael F. Cohen: colleagues