LEADER 02117nam 2200409 450 001 9910822328603321 005 20230809235053.0 010 $a3-8325-9264-4 035 $a(CKB)4340000000242262 035 $a(MiAaPQ)EBC5216221 035 $a5c7aad7d-cd78-461a-b757-7583b0dd2d03 035 $a(EXLCZ)994340000000242262 100 $a20180521d2017 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$a3D trajectory extraction from 2D videos for human activity analysis /$fZeyd Boukhers 210 1$aBerlin :$cLogos Verlag,$d[2017] 210 4$dİ2017 215 $a1 online resource (160 pages) 225 0 $aStudien zur Mustererkennung 300 $aPublicationDate: 20171126 311 $a3-8325-4583-2 330 $aLong description: The present dissertation addresses the problem of extracting 3D trajectories of objects from 2D videos. The reason of this is the theory that these trajectories symbolise high-level interpretations of human activities. A 3D trajectory of an object means its sequential positions in the real world over time. To this end, a generic framework for detecting objects and extracting their trajectories is proposed. In simpler terms, it means obtaining the 3D coordinate of the objects detected on the image plane and then tracking them in the real world to extract their 3D trajectories. Lastly, this dissertation presents applications of trajectory analysis to understand human activities in crowded environments. In this context, each phase in the framework represents independent approaches dedicated to solving challenging tasks in computer vision and multimedia. 606 $aImage processing$xDigital techniques 615 0$aImage processing$xDigital techniques. 676 $a621.367 700 $aBoukhers$b Zeyd$01690349 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910822328603321 996 $a3D trajectory extraction from 2D videos for human activity analysis$94065999 997 $aUNINA