Object 3D Reconstruction based on Photometric Stereo and Inverted Rendering
This addresses a specific limitation in photometric stereo for computer vision applications, representing an incremental advance.
The paper tackles the problem of 3D reconstruction from images under variable lighting, where indirect illumination causes biases in recovered shapes. It proposes an iterative photometric stereo method with inverted Monte-Carlo ray tracing to separate direct and indirect lighting, showing improvement over classic approaches on three datasets.
Methods for 3D reconstruction such as Photometric stereo recover the shape and reflectance properties using multiple images of an object taken with variable lighting conditions from a fixed viewpoint. Photometric stereo assumes that a scene is illuminated only directly by the illumination source. As result, indirect illumination effects due to inter-reflections introduce strong biases in the recovered shape. Our suggested approach is to recover scene properties in the presence of indirect illumination. To this end, we proposed an iterative PS method combined with a reverted Monte-Carlo ray tracing algorithm to overcome the inter-reflection effects aiming to separate the direct and indirect lighting. This approach iteratively reconstructs a surface considering both the environment around the object and its concavities. We demonstrate and evaluate our approach using three datasets and the overall results illustrate improvement over the classic PS approaches.