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Probabilistic Modeling of Multicamera Interference for Time-of-Flight Sensors.

Bryan Rodriguez1, Xinxiang Zhang1, Dinesh Rajan1

  • 1Department of Electrical and Computer Engineering, Lyle School of Engineering, Southern Methodist University, Dallas, TX 75205, USA.

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Summary
This summary is machine-generated.

Multicamera interference in 3D depth maps causes data loss. This study introduces a framework using probabilistic models and ray tracing to accurately predict and simulate this interference, aiding in developing mitigation strategies.

Keywords:
3D image processingdepth mapsmulticamera interferencetime-of-flight sensors

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Area of Science:

  • Computer Vision
  • 3D Imaging
  • Optical Physics

Background:

  • Multicamera interference in infrared (IR) 3D imaging is not well understood.
  • Interference leads to increased zero-value pixels in depth maps, causing loss of critical depth information.
  • This phenomenon impacts the reliability of 3D imaging systems.

Purpose of the Study:

  • To develop a framework for synthetically generating direct and indirect multicamera interference in 3D images.
  • To create a mathematical model that predicts the locations and probabilities of zero-value pixels caused by interference.
  • To enable better understanding and mitigation of multicamera interference in 3D depth sensing.

Main Methods:

  • A combination of a probabilistic model and ray tracing was used to generate synthetic interference.
  • A mathematical model was developed to predict zero-value pixel distribution in interfered depth maps.
  • Synthetic interference images were compared against controlled laboratory-captured images.

Main Results:

  • The framework accurately predicts the locations of lost depth information due to multicamera interference.
  • For direct interference, the framework achieved an average RMSE of 0.0625, PSNR of 24.1277 dB, and SSIM of 0.9007.
  • For indirect interference, the framework achieved an average RMSE of 0.0312, PSNR of 26.2280 dB, and SSIM of 0.9064.

Conclusions:

  • The proposed framework effectively simulates multicamera interference in 3D depth maps.
  • The model's accuracy in predicting zero-value pixels validates its utility.
  • This framework is essential for developing and testing techniques to mitigate interference, crucial for advancing 3D imaging technologies.