A self-calibrating method for photogeometric acquisition of 3D objects.

Area of Science:

• Computer Vision
• 3D Reconstruction
• Computational Imaging

Background:

• Traditional 3D scanning often requires complex, pre-calibrated systems.
• Existing methods typically separate geometric and photometric data acquisition.
• Digital cameras are limited to capturing images, not projecting light.

Purpose of the Study:

• To develop a self-calibrating photogeometric method for 3D model creation.
• To enable rapid and robust acquisition of high-resolution, colored 3D models using off-the-shelf hardware.
• To overcome the limitations of separate geometric and photometric data acquisition.

Main Methods:

• A novel self-calibrating, multiviewpoint 3D acquisition technique based on structured light.
• Simultaneous acquisition of surface position and surface normal data.
• Utilizing a digital projector as both an active light source and a virtual camera.

Main Results:

• Generation of multimillion point-sampled and colored 3D models of real-world objects.
• High-quality reconstructions achieved at camera resolution, not limited by projector resolution.
• Demonstrated successful capture of several detailed 3D models.

Conclusions:

• The proposed method offers a versatile and efficient approach to 3D model creation.
• The simultaneous use of a projector as both light source and virtual camera is a key innovation.
• This technique provides a robust and accessible solution for high-fidelity 3D scanning.