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020 _a9789811521096
_9978-981-15-2109-6
024 7 _a10.1007/978-981-15-2109-6
_2doi
050 4 _aH61.3
072 7 _aUF
_2bicssc
072 7 _aCOM005000
_2bisacsh
072 7 _aUXJ
_2thema
082 0 4 _a300.00285
_223
100 1 _aYu, Zhiwen.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aHuman Behavior Analysis: Sensing and Understanding
_h[electronic resource] /
_cby Zhiwen Yu, Zhu Wang.
250 _a1st ed. 2020.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2020.
300 _aX, 271 p. 92 illus., 70 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _a1. Introduction -- 2. Main Steps of Human Behavior Sensing and Understanding -- 3. Sensor-Based Behavior Recognition -- 4. Device-free Behavior Recognition -- 5. Individual Behavior Recognition -- 6. Group Behavior Recognition -- 7. Community Behavior Understanding -- 8. Open Issues and Emerging Trends.
520 _aOver the last decade, there has been a growing interest in human behavior analysis, motivated by societal needs such as security, natural interfaces, affective computing, and assisted living. However, the accurate and non-invasive detection and recognition of human behavior remain major challenges and the focus of many research efforts. Traditionally, in order to identify human behavior, it is first necessary to continuously collect the readings of physical sensing devices (e.g., camera, GPS, and RFID), which can be worn on human bodies, attached to objects, or deployed in the environment. Afterwards, using recognition algorithms or classification models, the behavior types can be identified so as to facilitate advanced applications. Although such traditional approaches deliver satisfactory performance and are still widely used, most of them are intrusive and require specific sensing devices, raising issues such as privacy and deployment costs. In this book, we will present our latest findings on non-invasive sensing and understanding of human behavior. Specifically, this book differs from existing literature in the following senses. Firstly, we focus on approaches that are based on non-invasive sensing technologies, including both sensor-based and device-free variants. Secondly, while most existing studies examine individual behaviors, we will systematically elaborate on how to understand human behaviors of various granularities, including not only individual-level but also group-level and community-level behaviors. Lastly, we will discuss the most important scientific problems and open issues involved in human behavior analysis.
650 0 _aSocial sciences
_xData processing.
650 0 _aData mining.
650 0 _aMicrocomputers.
650 1 4 _aComputer Application in Social and Behavioral Sciences.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aPersonal Computing.
700 1 _aWang, Zhu.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789811521089
776 0 8 _iPrinted edition:
_z9789811521102
776 0 8 _iPrinted edition:
_z9789811521119
856 4 0 _uhttps://doi.org/10.1007/978-981-15-2109-6
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
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