Time-of-Flight and Depth Imaging. Sensors, Algorithms and Applications Dagstuhl Seminar 2012 and GCPR Workshop on Imaging New Modalities /

Cameras for 3D depth imaging, using either time-of-flight (ToF) or structured light sensors, have received a lot of attention recently and have been improved considerably over the last few years. The present techniques make full-range 3D data available at video frame rates, and thus pave the way for...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Grzegorzek, Marcin (Editor ), Theobalt, Christian (Editor ), Koch, Reinhard (Editor ), Kolb, Andreas (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Edición:1st ed. 2013.
Colección:Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 8200
Temas:
Computer vision.
Pattern recognition systems.
Artificial intelligence.
Computer Vision.
Automated Pattern Recognition.
Artificial Intelligence.
Acceso en línea:Texto Completo

MARC

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245 1 0 |a Time-of-Flight and Depth Imaging. Sensors, Algorithms and Applications  |h [electronic resource] :  |b Dagstuhl Seminar 2012 and GCPR Workshop on Imaging New Modalities /  |c edited by Marcin Grzegorzek, Christian Theobalt, Reinhard Koch, Andreas Kolb. 
250 |a 1st ed. 2013. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2013. 
300 |a X, 319 p. 137 illus.  |b online resource. 
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490 1 |a Image Processing, Computer Vision, Pattern Recognition, and Graphics ;  |v 8200 
505 0 |a Part I: Foundations of Depth Imaging -- Technical Foundation and Calibration Methods for Time-of-Flight Cameras -- Denoising Strategies for Time-of-Flight Data -- Stabilization of 3D Position Measurement -- Ground Truth for Evaluating Time of Flight Imaging -- Part II: Depth Data Processing and Fusion -- Mirrors in Computer Graphics, Computer Vision and Time-of-Flight Imaging -- A Survey on Time-of-Flight Stereo Fusion -- Reconstruction of Deformation from Depth and Color Video with Explicit Noise Models -- Part III: Human-Centered Depth Imaging -- A Survey on Human Motion Analysis from Depth Data -- Full-Body Human Motion Capture from Monocular Depth Images -- Gesture Interfaces with Depth Sensors -- Real-Time Range Imaging in Health Care: A Survey -- Part IV: Proceedings of the Workshop on Imaging New Modalities -- A State of the Art Report on Kinect Sensor Setups in Computer Vision -- Real-Time Motion Artifact Compensation for PMD-ToF Images -- Real-Time Image Stabilization for ToF Cameras on Mobile Platforms -- On the Calibration of Focused Plenoptic Cameras. 
520 |a Cameras for 3D depth imaging, using either time-of-flight (ToF) or structured light sensors, have received a lot of attention recently and have been improved considerably over the last few years. The present techniques make full-range 3D data available at video frame rates, and thus pave the way for a much broader application of 3D vision systems. A series of workshops have closely followed the developments within ToF imaging over the years. Today, depth imaging workshops can be found at every major computer vision conference. The papers presented in this volume stem from a seminar on Time-of-Flight Imaging held at Schloss Dagstuhl in October 2012. They cover all aspects of ToF depth imaging, from sensors and basic foundations, to algorithms for low level processing, to important applications that exploit depth imaging. In addition, this book contains the proceedings of a workshop on Imaging New Modalities, which was held at the German Conference on Pattern Recognition in Saarbrücken, Germany, in September 2013. A state-of-the-art report on the Kinect sensor and its applications is followed by two reports on local and global ToF motion compensation and a novel depth capture system using a plenoptic multi-lens multi-focus camera sensor. 
650 0 |a Computer vision. 
650 0 |a Pattern recognition systems. 
650 0 |a Artificial intelligence. 
650 1 4 |a Computer Vision. 
650 2 4 |a Automated Pattern Recognition. 
650 2 4 |a Artificial Intelligence. 
700 1 |a Grzegorzek, Marcin.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a Theobalt, Christian.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a Koch, Reinhard.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a Kolb, Andreas.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
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950 |a Computer Science (R0) (SpringerNature-43710) 

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