Free Your Hands: Lightweight Turntable-Based Object Capture Pipeline

Abstract

Novel view synthesis (NVS) from multiple captured photos of an object is a widely studied problem. Achieving high quality typically requires dense sampling of input views, which can lead to frustrating manual labor. Manually positioning cameras to maintain an optimal desired distribution can be difficult for humans, and if a good distribution is found, it is not easy to replicate. Additionally, the captured data can suffer from motion blur and defocus due to human error. In this paper, we use a lightweight object capture pipeline to reduce the manual workload and standardize the acquisition setup, with a consumer turntable to carry the object and a tripod to hold the camera. Of course, turntables and gantry systems have been frequently used to automatically capture dense samples under various views and lighting conditions; the key difference is that we use a turntable under natural environment lighting. This way, we can easily capture hundreds of valid images in several minutes without hands-on effort. However, in the object reference frame, the light conditions vary (rotate); this does not match the assumptions of standard NVS methods like 3D Gaussian splatting (3DGS). We design a neural radiance representation conditioned on light rotations, which addresses this issue and allows rendering with novel light rotations as an additional benefit. We further study the behavior of rotations and find optimal capturing strategies. We demonstrate our pipeline using 3DGS as the underlying framework, achieving higher quality and showcasing the method's potential for novel lighting and harmonization tasks.