Photometric Stereo for Dynamic Surface Orientations

We present a photometric stereo method for non-rigid objects of unknown and spatially varying materials. The prior art uses time-multiplexed illumination but assumes constant surface normals across several frames, fundamentally limiting the accuracy of the estimated normals. We explicitly account for time-varying surface orientations, and show that for unknown Lambertian materials, five images are sufficient to recover surface orientation in one frame. Our optimized system implementation exploits the physical properties of typical cameras and LEDs to reduce the required number of images to just three, and also facilitates frame-to-frame image alignment using standard optical flow methods, despite varying illumination. We demonstrate the system's performance by computing surface orientations for several different moving, deforming objects.