Uncalibrated Multi-View Photometric Stereo with Ambient and Near-Light Illumination for High-Fidelity 3D Reconstruction
核心概念
This work introduces the first framework for multi-view uncalibrated point-light photometric stereo, combining state-of-the-art volume rendering with a physically realistic lighting model. It enables high-accuracy 3D reconstruction from sparse and distant viewpoints, even in real-world environments with ambient lighting, without requiring tedious laboratory setup or extensive training data.
要約
The paper proposes a novel framework for multi-view uncalibrated photometric stereo that combines state-of-the-art volume rendering techniques with a physically realistic lighting model. Key highlights:
-
It introduces the first framework for multi-view uncalibrated point-light photometric stereo, eliminating the need for a dark room environment, dense capturing process, and distant lighting assumptions.
-
The approach relaxes the dark room assumption and allows a combination of static ambient lighting and dynamic near LED lighting, enabling easy data capture outside the lab.
-
It validates that the proposed method can be successfully used for accurate shape reconstruction of textureless objects in highly sparse scenarios with wide baselines, outperforming cutting-edge approaches.
-
Despite the absence of pre-processing or vast training data, the framework outperforms methods that rely on static ambient illumination or photometric stereo imagery.
-
The paper presents an efficient strategy to handle the diffuse albedo, which significantly improves performance in extremely sparse scenarios with only two viewpoints.
The authors demonstrate the effectiveness of their approach through extensive experiments on both synthetic and real-world datasets, showcasing superior reconstruction quality compared to state-of-the-art methods.
Sparse Views, Near Light
統計
The paper does not provide any specific numerical data or statistics in the main text. The results are presented qualitatively through visual comparisons and quantitative evaluation metrics like RMSE and MAE.
引用
"We introduce the first framework for multi-view uncalibrated point-light photometric stereo. It combines a state-of-the-art volume rendering formulation with a physically realistic model of ambient light and point lights."
"We eliminate the need for a dark room environment, dense capturing process, and distant lighting. Thereby we enhance the accessibility and simplify data acquisition for setups beyond traditional laboratory settings."
"Despite the absence of pre-processing or vast training data, we outperform cutting-edge approaches that either rely only on static ambient illumination or PS imagery."
深掘り質問
How could the proposed framework be extended to handle dynamic scenes or non-rigid objects?
To extend the proposed framework to handle dynamic scenes or non-rigid objects, several modifications and enhancements could be implemented:
Dynamic Scene Handling:
Introduce a mechanism to track the motion of dynamic objects in the scene over time. This could involve incorporating techniques from computer vision such as optical flow or object tracking to estimate the movement of objects.
Implement a temporal consistency constraint to ensure that the reconstructed geometry remains coherent across different frames in a dynamic scene.
Non-Rigid Object Handling:
Modify the geometry representation to accommodate non-rigid deformations. This could involve using deformable models or mesh-based representations that can adapt to the changing shape of non-rigid objects.
Incorporate techniques from non-rigid structure from motion to estimate the deformations of non-rigid objects from multiple viewpoints.
Dynamic Lighting:
Extend the lighting model to handle dynamic lighting conditions. This could involve incorporating information about changing light sources or varying ambient lighting in the scene.
Develop algorithms to estimate the dynamic lighting conditions and integrate them into the reconstruction process.
