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.
@inproceedings{e2019optimizing, title={Optimizing Portrait Lighting at Capture-Time Using a 360 Camera as a Light Probe}, author={E, Jane L. and Fried, Ohad and Agrawala, Maneesh}, booktitle={Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology}, url = {https://dl.acm.org/doi/10.1145/3332165.3347893}, doi = {10.1145/3332165.3347893}, pages={221--232}, year={2019}, organization={ACM}, series = {UIST ’19} }