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

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 tells the photographer how far to rotate about the subject and provides real-time feedback showing how close the photographer's current view is to the view at the target orientation. 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 is very useful and reduces the mental effort required by photographers to produce well-lit portraits. We discuss why our approach is suitable for implementation directly in camera hardware.