Optimizing Portrait Lighting at Capture-Time Using a 360 Camera as a Light Probe

Jane L. E, Ohad Fried, Maneesh Agrawala
UIST: Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology, 2019
We present a capture-time tool designed to help casual photog- raphers orient their subject to achieve a user-specified target facial appearance. The inputs to our tool are an HDR envi- ronment map of the scene captured using a 360 camera, and a target facial appearance, selected from a gallery of com- mon 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.