A REVIEW ON COMMERCIAL SOLID STATE 3 D CAMERAS FOR MACHINE VISION APPLICATIONS

Perception of the environment in 3D has always been an important sensory input for machine vision applications. 3D imaging sensors have been investigated for several decades. Recently, novel solid state 3D technologies have emerged, leading to 3D vision systems with radically improved characteristics. At present these new technologies make full-range 3D data available at high frame rates, and thus open the path toward a much broader application of 3D vision systems for machine vision applications. This book chapter reviews state-of-the-art commercial solid state 3D cameras and presents their working principle, their range measurement precision and linearity, and typical machine vision applications. At the end of the book chapter the pro and cons of each technology are listed and the latest camera model of each technology is presented. Hence the reader will be aided in selecting the most suitable 3D camera for a given machine vision application. Furthermore the advantages of a 3D vision system over a conventional 2D vision system are demonstrated through the examples.

[1]  P. Hanrahan,et al.  Light Field Photography with a Hand-held Plenoptic Camera , 2005 .

[2]  Robert Lange,et al.  3D time-of-flight distance measurement with custom solid-state image sensors in CMOS/CCD-technology , 2006 .

[3]  Stephan Hussmann,et al.  One-Phase Algorithm for Continuous Wave TOF Machine Vision Applications , 2013, IEEE Transactions on Instrumentation and Measurement.

[4]  Reinhard Koch,et al.  Time-of-Flight sensor calibration for accurate range sensing , 2010, Comput. Vis. Image Underst..

[5]  Chintan Intwala,et al.  Light Field Camera Design for Integral View Photography , 2006 .

[6]  Bedrich J. Hosticka,et al.  Modeling and calibration of 3D-Time-of-Flight pulse-modulated image sensors , 2011, 2011 20th European Conference on Circuit Theory and Design (ECCTD).

[7]  A. Lumsdaine.  Full Resolution Lightfield Rendering , 2008 .

[8]  Stephan Hussmann,et al.  Real-Time Processing of 3D-TOF Data in Machine Vision Applications , 2012 .

[9]  Dr.-Ing. Thorsten Ringbeck.  A 3 D TIME OF FLIGHT CAMERA FOR OBJECT DETECTION , 2007 .

[10]  M. Johannesson.  Can sorting using sheet-of-light range imaging and MAPP2200 , 1993, Proceedings of IEEE Systems Man and Cybernetics Conference - SMC.

[11]  Herbert E. Ives,et al.  A Camera for Making Parallax Panoramagrams , 1928 .

[12]  Stephan Hussmann,et al.  Pseudo-Four-Phase-Shift Algorithm for Performance Enhancement of 3D-TOF Vision Systems , 2010, IEEE Transactions on Instrumentation and Measurement.

[13]  Stephan Hussmann,et al.  A Performance Review of 3D TOF Vision Systems in Comparison to Stereo Vision Systems , 2008 .

[14]  Robert Forchheimer,et al.  A Single Chip Linear Array Picture Processor , 1983, Other Conferences.

[15]  B. Buttgen,et al.  Demodulation Pixel Based on Static Drift Fields , 2006, IEEE Transactions on Electron Devices.

[16]  Ray A. Jarvis,et al.  A Perspective on Range Finding Techniques for Computer Vision , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Robert Forchheimer,et al.  MAPP2200 Smart Vision Sensor. Programmability and Adaptivity , 1992, MVA.

[18]  Helmut Fischer,et al.  New electro-optical mixing and correlating sensor: facilities and applications of the photonic mixer device (PMD) , 1997, Other Conferences.

[19]  Lennart Wietzke,et al.  Single lens 3D-camera with extended depth-of-field , 2012, Electronic Imaging.

[20]  Gongzhu Hu,et al.  3-D Surface Solution Using Structured Light and Constraint Propagation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  Joachim Hertzberg,et al.  Automatic model refinement for 3D reconstruction with mobile robots , 2003, Fourth International Conference on 3-D Digital Imaging and Modeling, 2003. 3DIM 2003. Proceedings..

[22]  Izhal Abdul Halin,et al.  A review on Solid State time of flight TOF range image sensors , 2009, 2009 IEEE Student Conference on Research and Development (SCOReD).

[23]  Robert Forchheimer,et al.  MAPP2200: a second-generation smart optical sensor , 1992, Electronic Imaging.

[24]  R. Johansson,et al.  A multiresolution 100-GOPS 4-Gpixels/s programmable smart vision sensor for multisense imaging , 2005, IEEE Journal of Solid-State Circuits.