LEADER 03008nam 22004575 450 001 9910484331403321 005 20220914205925.0 010 $a3-030-31852-4 024 7 $a10.1007/978-3-030-31852-9 035 $a(CKB)4100000009522913 035 $a(MiAaPQ)EBC6111744 035 $a(DE-He213)978-3-030-31852-9 035 $a(PPN)243768605 035 $a(EXLCZ)994100000009522913 100 $a20191011d2020 fy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aIndoor scene recognition by 3-D object search $efor robot programming by demonstration /$fPascal Meißner 205 $a1st edition 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (xix, 262 pages) $cillustrations (some color) 225 1 $aSpringer Tracts in Advanced Robotics,$x1610-7438 ;$v135 311 1 $a3-030-31851-6 320 $aIncludes bibliographical references. 327 $aIntroduction -- RelatedWork -- PassiveSceneRecognition -- ActiveSceneRecognition -- Evaluation -- Summary -- Appendix. . 330 $aThis book focuses on enabling mobile robots to recognize scenes in indoor environments, in order to allow them to determine which actions are appropriate at which points in time. In concrete terms, future robots will have to solve the classification problem represented by scene recognition sufficiently well for them to act independently in human-centered environments. To achieve accurate yet versatile indoor scene recognition, the book presents a hierarchical data structure for scenes ? the Implicit Shape Model trees. Further, it also provides training and recognition algorithms for these trees. In general, entire indoor scenes cannot be perceived from a single point of view. To address this problem the authors introduce Active Scene Recognition (ASR), a concept that embeds canonical scene recognition in a decision-making system that selects camera views for a mobile robot to drive to so that it can find objects not yet localized. The authors formalize the automatic selection of camera views as a Next-Best-View (NBV) problem to which they contribute an algorithmic solution, which focuses on realistic problem modeling while maintaining its computational efficiency. Lastly, the book introduces a method for predicting the poses of objects to be searched, establishing the otherwise missing link between scene recognition and NBV estimation. 410 0$aSpringer Tracts in Advanced Robotics,$x1610-7438 ;$v135 606 $aRobots$xProgramming 615 0$aRobots$xProgramming. 676 $a629.89251 700 $aMeißner$b Pascal$4aut$4http://id.loc.gov/vocabulary/relators/aut$0857567 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484331403321 996 $aIndoor Scene Recognition by 3-D Object Search$91914848 997 $aUNINA