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Related Experiment Video

Updated: May 11, 2026

Medical-grade Sterilizable Target for Fluid-immersed Fetoscope Optical Distortion Calibration

Medical-grade Sterilizable Target for Fluid-immersed Fetoscope Optical Distortion Calibration

Published on: February 23, 2017

Camera calibration with active phase target: improvement on feature detection and optimization.

Lei Huang¹, Qican Zhang, Anand Asundi

¹School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore.

|May 2, 2013

Summary

This summary is machine-generated.

This study enhances camera calibration for optical metrology using an active phase target and statistically constrained bundle adjustment (SCBA). The methods improve feature detection and reduce reprojection errors to 0.0067 pixels.

Related Experiment Videos

Last Updated: May 11, 2026

Medical-grade Sterilizable Target for Fluid-immersed Fetoscope Optical Distortion Calibration

Medical-grade Sterilizable Target for Fluid-immersed Fetoscope Optical Distortion Calibration

Published on: February 23, 2017

Area of Science:

Optical metrology
Computer vision
Image processing

Background:

Camera calibration is crucial for 3D reconstruction in optical metrology.
Existing methods face challenges in feature detection and precise parameter optimization.
Active phase targets offer potential for improved calibration accuracy.

Purpose of the Study:

To enhance camera calibration techniques for intrinsic and extrinsic parameters.
To investigate improvements in feature detection and overall optimization using novel methods.
To reduce the complexity of active target measurement in calibration procedures.

Main Methods:

Utilizing an active phase target with sinusoidal fringe patterns.
Implementing "virtual defocusing" and windowed polynomial fitting for feature detection.
Applying statistically constrained bundle adjustment (SCBA) for optimization.

Main Results:

Enhanced feature detection accuracy using the proposed methods.
Successful application of SCBA, eliminating the need for difficult active target measurements.
Achieved a root mean square reprojection error of 0.0067 pixels in experimental calibration.

Conclusions:

The proposed methods significantly improve camera calibration accuracy and efficiency.
Virtual defocusing and windowed polynomial fitting are effective for feature detection with active phase targets.
Statistically constrained bundle adjustment provides a robust optimization framework for camera calibration.