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Identification and correction of flying pixels in range camera data

Published: 21 April 2008 Publication History

Abstract

This paper focuses on errors which are possible to occur in the depth measurements of range cameras. Range cameras can capture 3D information of a scene by sending out infrared light and then measuring the reflections. Wrong measurements occur at the edges of objects where the depth level changes. A depth value between the foreground and background level is measured which creates a so-called "flying pixel" when displaying the 3D points.
In this paper different methods for the identification of flying pixels are presented and compared. The advantages and drawbacks of each method are discussed. Then a simple method for the correction of flying pixel errors is presented and its limitations are shown. The final method for correction is presented which is based on segmenting the pixel matrix into horizontal and vertical scanlines. After segmentation, linear segments can be identified to which the pixels can be mapped. The paper concludes with the evaluation of the presented methods to show their effectiveness.

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Jiang, X., Bunke, H. 1999. Edge Detection in Range Images Based on Scan Line Approximation. Proceedings of the Conference on Computer Vision and Image Understanding, Vol. 73, No. 2, 183--199.
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Lange, R. 2000. 3D Time-of-Flight Distance Measurement with Custom Solid-State Image Sensors in CMOS/CCD-Technology, Dissertation, University Siegen.
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Lindner, M. and Kolb, A. 2006. Lateral and Depth Calibration of PMD-Distance Sensors, Proc. International Symposium on Visual Computing (ISVC06), Lake Tahoe, Nevada, USA, 524--533.
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Lindner, M. Lambers, M., Kolb, A. 2007. Sub-Pixel Data Fusion and Edge-Enhanced Distance Refinement for 2D/3D Images. Proceedings of the Conference on Dynamic 3D Imaging Workshop in Conjunction with DAGM, Heidelberg, Germany, 94--103.
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Cited By

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  • (2024)High-Throughput and Accurate 3D Scanning of Cattle Using Time-of-Flight Sensors and Deep LearningSensors10.3390/s2416527524:16(5275)Online publication date: 14-Aug-2024
  • (2024)Object pose and surface material recognition using a single-time-of-flight cameraAdvanced Photonics Nexus10.1117/1.APN.3.5.0560013:05Online publication date: 1-Sep-2024
  • (2024)Color-Guided Flying Pixel Correction in Depth Images2024 IEEE 26th International Workshop on Multimedia Signal Processing (MMSP)10.1109/MMSP61759.2024.10743790(1-6)Online publication date: 2-Oct-2024
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cover image ACM Other conferences
SCCG '08: Proceedings of the 24th Spring Conference on Computer Graphics
April 2008
196 pages
ISBN:9781605589572
DOI:10.1145/1921264
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • Comenius University: Comenius University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 April 2008

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Author Tags

  1. PMD
  2. flying pixels
  3. flying surfels
  4. range camera
  5. range data
  6. segmentation

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  • Research-article

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SCCG08
Sponsor:
  • Comenius University
SCCG08: Spring Conference on Computer Graphics
April 21 - 23, 2008
Budmerice, Slovakia

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Overall Acceptance Rate 67 of 115 submissions, 58%

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Cited By

View all
  • (2024)High-Throughput and Accurate 3D Scanning of Cattle Using Time-of-Flight Sensors and Deep LearningSensors10.3390/s2416527524:16(5275)Online publication date: 14-Aug-2024
  • (2024)Object pose and surface material recognition using a single-time-of-flight cameraAdvanced Photonics Nexus10.1117/1.APN.3.5.0560013:05Online publication date: 1-Sep-2024
  • (2024)Color-Guided Flying Pixel Correction in Depth Images2024 IEEE 26th International Workshop on Multimedia Signal Processing (MMSP)10.1109/MMSP61759.2024.10743790(1-6)Online publication date: 2-Oct-2024
  • (2023)On the Formulation of Coded Demodulation and 3D Reconstruction in Rotating PB-ToF sensors2023 31st European Signal Processing Conference (EUSIPCO)10.23919/EUSIPCO58844.2023.10289925(1943-1947)Online publication date: 4-Sep-2023
  • (2023)Performance Evaluation of State-of-the-Art High-Resolution Time-of-Flight CamerasIEEE Sensors Journal10.1109/JSEN.2023.327316523:12(13711-13727)Online publication date: 15-Jun-2023
  • (2022)Relative Pose Estimation of Non-Cooperative Space Targets Using a TOF CameraRemote Sensing10.3390/rs1423610014:23(6100)Online publication date: 1-Dec-2022
  • (2021)Mask-ToF: Learning Microlens Masks for Flying Pixel Correction in Time-of-Flight Imaging2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR46437.2021.00900(9112-9122)Online publication date: Jun-2021
  • (2019)Dealing with Missing Depth: Recent Advances in Depth Image Completion and EstimationRGB-D Image Analysis and Processing10.1007/978-3-030-28603-3_2(15-50)Online publication date: 27-Oct-2019
  • (2018)Variational Fusion of Time-of-Flight and Stereo Data for Depth Estimation Using Edge-Selective Joint FilteringIEEE Transactions on Multimedia10.1109/TMM.2018.282588320:11(2882-2890)Online publication date: Nov-2018
  • (2016)Spatio-Temporal Denoising for Depth Map SequencesInternational Journal of Multimedia Data Engineering & Management10.4018/IJMDEM.20160401027:2(21-35)Online publication date: 1-Apr-2016
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