Name
Abstract | ||
|---|---|---|
We present a capture-time tool designed to help casual photographers orient their subject to achieve a user-specified target facial appearance. The inputs to our tool are an HDR environment map of the scene captured using a 360 camera, and a target facial appearance, selected from a gallery of common studio lighting styles. Our tool computes the optimal orientation for the subject to achieve the target lighting using a computationally efficient precomputed radiance transfer-based approach. It then tells the photographer how far to rotate about the subject. Optionally, our tool can suggest how to orient a secondary external light source (e.g. a phone screen) about the subject's face to further improve the match to the target lighting. We demonstrate the effectiveness of our approach in a variety of indoor and outdoor scenes using many different subjects to achieve a variety of looks. A user evaluation suggests that our tool reduces the mental effort required by photographers to produce well-lit portraits.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3332165.3347893 | Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology |
Keywords | Field | DocType |
360 camera, environment map, portrait lighting | Computer graphics (images),Computer science,Portrait,Human–computer interaction | Conference |
ISBN | Citations | PageRank |
978-1-4503-6816-2 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| L. E. Jane | 1 | 78 | 6.40 |
| Ohad Fried | 2 | 101 | 7.20 |
| Maneesh Agrawala | 3 | 5192 | 333.08 |