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Time-of-Flight Cameras [electronic resource] : Principles, Methods and Applications / by Miles Hansard, Seungkyu Lee, Ouk Choi, Radu Horaud.

Por: Colaborador(es): Tipo de material: TextoTextoSeries SpringerBriefs in Computer Science | SpringerBriefs in Computer ScienceEditor: London : Springer London : Imprint: Springer, 2013Descripción: X, 96 p. 55 illus., 19 illus. in color. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • online resource
ISBN:
  • 9781447146582
Trabajos contenidos:
  • SpringerLink (Online service)
Tema(s): Formatos físicos adicionales: Sin títuloClasificación CDD:
  • 006.6 23
  • 006.37 23
Clasificación LoC:
  • TA1637-1638
  • TA1637-1638
Recursos en línea:
Contenidos:
Springer eBooksResumen: Time-of-flight (TOF) cameras provide a depth value at each pixel, from which the 3D structure of the scene can be estimated. This new type of active sensor makes it possible to go beyond traditional 2D image processing, directly to depth-based and 3D scene processing. Many computer vision and graphics applications can benefit from TOF data, including 3D reconstruction, activity and gesture recognition, motion capture and face detection. It is already possible to use multiple TOF cameras, in order to increase the scene coverage, and to combine the depth data with images from several colour cameras. Mixed TOF and colour systems can be used for computational photography, including full 3D scene modelling, as well as for illumination and depth-of-field manipulations. This work is a technical introduction to TOF sensors, from architectural and design issues, to selected image processing and computer vision methods.
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Characterization of Time-of-Flight Data -- Disambiguation of Time-of-Flight Data -- Calibration of Time-of-Flight Cameras -- Alignment of Time-of-Flight and Stereoscopic Data -- A Mixed Time-of-Flight and Stereoscopic Camera System.

Time-of-flight (TOF) cameras provide a depth value at each pixel, from which the 3D structure of the scene can be estimated. This new type of active sensor makes it possible to go beyond traditional 2D image processing, directly to depth-based and 3D scene processing. Many computer vision and graphics applications can benefit from TOF data, including 3D reconstruction, activity and gesture recognition, motion capture and face detection. It is already possible to use multiple TOF cameras, in order to increase the scene coverage, and to combine the depth data with images from several colour cameras. Mixed TOF and colour systems can be used for computational photography, including full 3D scene modelling, as well as for illumination and depth-of-field manipulations. This work is a technical introduction to TOF sensors, from architectural and design issues, to selected image processing and computer vision methods.

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