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020 _a9781461454861
_9978-1-4614-5486-1
024 7 _a10.1007/978-1-4614-5486-1
_2doi
050 4 _aTA1637-1638
050 4 _aTA1634
072 7 _aUYT
_2bicssc
072 7 _aUYQV
_2bicssc
072 7 _aCOM012000
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072 7 _aCOM016000
_2bisacsh
082 0 4 _a006.6
_223
082 0 4 _a006.37
_223
100 1 _aAmato, Alberto.
_eauthor.
245 1 0 _aSemantic Analysis and Understanding of Human Behavior in Video Streaming
_h[electronic resource] /
_cby Alberto Amato, Vincenzo Di Lecce, Vincenzo Piuri.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aXII, 108 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aIntroduction -- Sensors for Human Behavior Analysis -- Related Works -- Sensor Data Interpretation for Symbolic Analysis -- Semantic Analysis -- Evaluation of the proposed methodology -- Conclusions.
520 _aSemantic Analysis and Understanding of Human Behaviour in Video Streaming investigates the semantic analysis of the human behaviour captured by video streaming, and introduces both theoretical and technological points of view. Video analysis based on the semantic content is in fact still an open issue for the computer vision research community, especially when real-time analysis of complex scenes is concerned.   This book explores an innovative, original approach to human behaviour analysis and understanding by using the syntactical symbolic analysis of images and video streaming described by means of strings of symbols. A symbol is associated to each area of the analyzed scene. When a moving object enters an area, the corresponding symbol is appended to the string describing the motion. This approach allows for characterizing the motion of a moving object with a word composed by symbols. By studying and classifying these words we can categorize and understand the various behaviours. The main advantage of this approach lies in the simplicity of the scene and motion descriptions so that the behaviour analysis will have limited computational complexity due to the intrinsic nature both of the representations and the related operations used to manipulate them. Besides, the structure of the representations is well suited for possible parallel processing, thus allowing for speeding up the analysis when appropriate hardware architectures are used. A new methodology for design systems for hierarchical high semantic level analysis of video streaming in narrow domains is also proposed.  Guidelines to design your own system are provided in this book.   Designed for practitioners, computer scientists and engineers working within the fields of human computer interaction, surveillance, image processing and computer vision, this book can also be used as secondary text book for advanced-level students in computer science and engineering.  .
650 0 _aComputer science.
650 0 _aMultimedia information systems.
650 0 _aUser interfaces (Computer systems).
650 0 _aArtificial intelligence.
650 0 _aImage processing.
650 0 _aPattern recognition.
650 1 4 _aComputer Science.
650 2 4 _aImage Processing and Computer Vision.
650 2 4 _aMultimedia Information Systems.
650 2 4 _aUser Interfaces and Human Computer Interaction.
650 2 4 _aPattern Recognition.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aDi Lecce, Vincenzo.
_eauthor.
700 1 _aPiuri, Vincenzo.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461454854
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-5486-1
912 _aZDB-2-SCS
942 _cEBK
999 _c56450
_d56450