Complete and faithful digital reconstruction of the real world is critical to many applications, such as virtual and augmented reality, holographic rendering, autonomous driving, digital cultural heritage preservation, virtual architecture and interior design. The physical world consists of objects made with different materials that give them diverse appearances. Scanning a scene with high visual diversity is challenging. All existing 3D scanning systems are limited to specific types of surfaces that they can work for. For example, some only works for the matte surfaces while some are designed for highly reflective ones. Therefore, there is need to devise a generic solution for digitalizing the real-world surfaces with diverse appearances. This project will result in an integrated solution for reconstructing general surfaces, regardless of their appearances. The outcome will significantly simplify the 3D scanning procedure and allow wide use of this technology by the general public. In addition, this research will be integrated into the curricula of new courses on computer vision and computational imaging at Louisiana State University.

This project will develop robust, fast, and accurate polarization-based imaging system for reconstructing general surfaces, ranging from diffuse to purely specular. This research is motivated by the fact that the polarization state of light embeds essential information on light transport. To achieve the goal, this project has two research thrusts: 1) formulate a polarization-inclusive light transport framework and 2) develop a practical system for reconstructing general surfaces. The first thrust will characterize the transformation of polarization after light interacts with surfaces of various reflectance properties. This framework provides the theoretical foundation for system development. The second thrust will design new programmable polarization-coded light sources and cameras, by leveraging recent advances in polarization sensors and optics. New physics-based 3D surface reconstruction algorithms will be developed through polarization analysis. Result of this project is expected to breakthrough major limitations of existing 3D scanning technology on general applicability. applicability.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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Louisiana State University
Baton Rouge
United States
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