LEADER 04609nam 2201441z- 450 001 9910619469003321 005 20221025 010 $a3-0365-5074-7 035 $a(CKB)5670000000391584 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/93177 035 $a(oapen)doab93177 035 $a(EXLCZ)995670000000391584 100 $a20202210d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aIntelligent Sensors for Human Motion Analysis 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 online resource (382 p.) 311 08$a3-0365-5073-9 330 $aThe book, "Intelligent Sensors for Human Motion Analysis," contains 17 articles published in the Special Issue of the Sensors journal. These articles deal with many aspects related to the analysis of human movement. New techniques and methods for pose estimation, gait recognition, and fall detection have been proposed and verified. Some of them will trigger further research, and some may become the backbone of commercial systems. 606 $aHistory of engineering and technology$2bicssc 606 $aTechnology: general issues$2bicssc 610 $a3D human mesh reconstruction 610 $a3D human pose estimation 610 $a3D multi-person pose estimation 610 $aabsolute poses 610 $aaction units 610 $aaggregation function 610 $aanomaly detection 610 $aartifact classification 610 $aartifact detection 610 $aartificial intelligence 610 $aassessment 610 $aAzure Kinect 610 $abalance 610 $aBerg Balance Scale 610 $aBILSTM 610 $abiometrics 610 $acamera-centric coordinates 610 $acomputer vision 610 $aconvolutional neural networks 610 $aCOVID-19 610 $acyber-physical systems 610 $adata augmentation 610 $adeep learning 610 $adeep neural network 610 $adeep-learning 610 $adevelopment 610 $adiagnosis 610 $aelderly 610 $aEMG 610 $aF-Formation 610 $afacial expression recognition 610 $afacial landmarks 610 $afall risk detection 610 $afeatures fusion 610 $afeatures selection 610 $aFFNN 610 $aFMCW 610 $afuzzy inference 610 $agait analysis 610 $agait parameters 610 $agait recognition 610 $agap filling 610 $ageneralization 610 $agraph convolutional networks 610 $agrey wolf optimization 610 $aGRU 610 $ahuman action recognition 610 $ahuman motion analysis 610 $ahuman motion modelling 610 $ahuman tracking 610 $aKinect v2 610 $akinematics 610 $aknowledge measure 610 $aLSTM 610 $amachine learning 610 $amarkerless 610 $amarkerless motion capture 610 $aMFCC 610 $amodular sensing unit 610 $amotion capture 610 $amovement tracking 610 $an/a 610 $aneural networks 610 $aoptical sensing principle 610 $aparticle swarm optimization 610 $apattern recognition 610 $aplantar pressure measurement 610 $apose estimation 610 $aposture detection 610 $aprecedence indicator 610 $arecognition 610 $areconstruction 610 $aregularized discriminant analysis 610 $aRGB-D sensors 610 $arobot 610 $arule induction 610 $askeletal data 610 $asocially occupied space 610 $atelemedicine 610 $atime series classification 610 $avital sign 610 $awhale optimization algorithm 610 $aXGBoost 610 $aZed 2i 615 7$aHistory of engineering and technology 615 7$aTechnology: general issues 700 $aKrzeszowski$b Tomasz$4edt$01314140 702 $aS?witon?ski$b Adam$4edt 702 $aKepski$b Michal$4edt 702 $aCalafate$b Carlos Tavares$4edt 702 $aKrzeszowski$b Tomasz$4oth 702 $aS?witon?ski$b Adam$4oth 702 $aKepski$b Michal$4oth 702 $aCalafate$b Carlos Tavares$4oth 906 $aBOOK 912 $a9910619469003321 996 $aIntelligent Sensors for Human Motion Analysis$93031756 997 $aUNINA