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Multimedia Techniques for Device and Ambient Intelligence [electronic resource] /edited by Jechang Jeong, Ernesto Damiani.

by Jeong, Jechang [editor.]; Damiani, Ernesto [editor.]; SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Boston, MA : Springer US, 2009.Description: online resource.ISBN: 9780387887777.Subject(s): Computer science | Computer Communication Networks | Information storage and retrieval systems | Multimedia systems | Artificial intelligence | Computer vision | Computer Science | Computer Communication Networks | Information Storage and Retrieval | Artificial Intelligence (incl. Robotics) | Multimedia Information Systems | Signal, Image and Speech Processing | Computer Imaging, Vision, Pattern Recognition and GraphicsOnline resources: Click here to access online
Contents:
Low Level Approach for Image and Video Understanding -- GOP Structure Conversion in Transcoding MPEG-2 to H.264/AVC -- Simple Low Level Features for Image Analysis -- Fast and robust Face Detection -- Automatic 3D Facial Fitting for Tracking in Video Sequence -- Multimedia Knowledge-Based Approaches and Applications -- Input Devices and Interaction Techniques for VR-Enhanced Medicine -- Bridging Sensing and Decision Making in Ambient Intelligence Environments -- Ambient Intelligence in Multimeda and Virtual Reality Environments for the rehabilitation -- Artificial Neural Networks for Processing Graphs with Application to Image Understanding: A Survey.
In: Springer eBooksSummary: Ambient Intelligence is a vision of the future where the world will be surrounded by electronic environments sensitive and responsive to people, wherein devices work in concert to support people in carrying out their everyday life activities, in an easy and natural way. This edited volume is based on the workshop Multimedia Techniques for Ambient Intelligence (MTDAI08), held in Mogliano Veneto, Italy in March 2008. Contributed by world renowned leaders in the field from academia and industry, this volume is dedicated to research on technologies used to improve the intelligence capability of multimedia devices for imaging, image processing and computer vision. Focuses on recent developments in digital signal processing, including evolutions in audiovisual signal processing, analysis, coding and authentication, and retrieval techniques. Designed for researchers and professionals, this book is also suitable for advanced-level students in computer science and electrical engineering.
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Low Level Approach for Image and Video Understanding -- GOP Structure Conversion in Transcoding MPEG-2 to H.264/AVC -- Simple Low Level Features for Image Analysis -- Fast and robust Face Detection -- Automatic 3D Facial Fitting for Tracking in Video Sequence -- Multimedia Knowledge-Based Approaches and Applications -- Input Devices and Interaction Techniques for VR-Enhanced Medicine -- Bridging Sensing and Decision Making in Ambient Intelligence Environments -- Ambient Intelligence in Multimeda and Virtual Reality Environments for the rehabilitation -- Artificial Neural Networks for Processing Graphs with Application to Image Understanding: A Survey.

Ambient Intelligence is a vision of the future where the world will be surrounded by electronic environments sensitive and responsive to people, wherein devices work in concert to support people in carrying out their everyday life activities, in an easy and natural way. This edited volume is based on the workshop Multimedia Techniques for Ambient Intelligence (MTDAI08), held in Mogliano Veneto, Italy in March 2008. Contributed by world renowned leaders in the field from academia and industry, this volume is dedicated to research on technologies used to improve the intelligence capability of multimedia devices for imaging, image processing and computer vision. Focuses on recent developments in digital signal processing, including evolutions in audiovisual signal processing, analysis, coding and authentication, and retrieval techniques. Designed for researchers and professionals, this book is also suitable for advanced-level students in computer science and electrical engineering.

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