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High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

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Performance model of depth from defocus with an unconventional camera.

P Trouvé-Peloux, F Champagnat, G Le Besnerais

Journal of the Optical Society of America. A, Optics, Image Science, and Vision

|October 6, 2021

Summary

We developed a generic model to assess depth from defocus (DFD) accuracy using a sensor's point spread function. This model works for any system and was validated on unconventional cameras for UAV navigation.

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Area of Science:

Computer Vision
Optical Engineering
Robotics

Background:

Depth estimation is crucial for autonomous systems like UAVs.
Depth from Defocus (DFD) offers a passive approach to depth sensing.
Existing DFD methods often lack a generalized performance evaluation framework.

Purpose of the Study:

To introduce a generic performance model for evaluating depth estimation accuracy in Depth from Defocus (DFD) systems.
To enable theoretical accuracy assessment using only the sensor's point spread function at a specific depth.
To facilitate the design and optimization of DFD systems for diverse applications.

Main Methods:

Developed a generic performance model based on the sensor point spread function (PSF).
Validated the model experimentally using two unconventional DFD cameras: one with a coded aperture and another with a chromatic aberration lens.
Applied the model to the end-to-end design of a 3D camera for UAV navigation.

Main Results:

The proposed model accurately predicts the theoretical accuracy of depth estimation.
Experimental validation confirmed the model's effectiveness on unconventional DFD systems.
The model guided the successful design of a 3D camera for small UAVs.

Conclusions:

The generic performance model provides a valuable tool for DFD system analysis and design.
The model's applicability extends to both conventional and unconventional DFD setups.
This work contributes to improved depth sensing capabilities for autonomous navigation systems.