Resolving Multi-path Interference in Time-of-Flight Imaging via Modulation Frequency Diversity and Sparse Regularization
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Abstract (arXiv)
Time-of-flight (ToF) cameras calculate depth maps by reconstructing phase shifts of amplitude-modulated signals. For broad illumination or transparent objects, reflections from multiple scene points can illuminate a given pixel, giving rise to an erroneous depth map. We report here a sparsity regularized solution that separates K-interfering components using multiple modulation frequency measurements. The method maps ToF imaging to the general framework of spectral estimation theory and has applications in improving depth profiles and exploiting multiple scattering.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Apr 2014.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 2; 2024: 1.
6 papers.
- 2024Depth Prompting for Sensor-Agnostic Depth Estimationcited by 26
- 2021Joint Depth and Normal Estimation from Real-world Time-of-flight Raw Datacited by 3
- 2023Self-Annotated 3D Geometric Learning for Smeared Points Removalcited by 3
- 2022Swept-Angle Synthetic Wavelength Interferometrycited by 2
- 2023ICET Online Accuracy Characterization for Geometry-Based Laser Scan Matchingcited by 1
- 2021Centimeter-Wave Free-Space Time-of-Flight Imagingcited by 0
- 2024Depth Prompting for Sensor-Agnostic Depth Estimation20 May 2024
- 2023Self-Annotated 3D Geometric Learning for Smeared Points Removal15 Nov 2023
- 2023ICET Online Accuracy Characterization for Geometry-Based Laser Scan Matching14 Jun 2023
- 2022Swept-Angle Synthetic Wavelength Interferometry21 May 2022
- 2021Joint Depth and Normal Estimation from Real-world Time-of-flight Raw Data8 Aug 2021
- 2021Centimeter-Wave Free-Space Time-of-Flight Imaging25 May 2021