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LEADER 00000cam  2200517Ii 4500 
001    1123192214 
003    OCoLC 
005    20191108044515.4 
006    m     o  d         
007    cr cnu|||unuuu 
008    191016s2020    sz a    ob    000 0 eng d 
019    1125996115|a1126342152|a1126640489 
020    9783030318529|q(electronic bk.) 
020    3030318524|q(electronic bk.) 
020    |z9783030318512|q(print) 
020    |z3030318516 
024 7  10.1007/978-3-030-31852-9|2doi 
024 7  10.1007/978-3-030-31 
035    (OCoLC)1123192214|z(OCoLC)1125996115|z(OCoLC)1126342152
       |z(OCoLC)1126640489 
040    GW5XE|beng|erda|epn|cGW5XE|dLQU|dOCLCF|dYDX 
049    MAIN 
050  4 TJ211.45 
082 04 629.8/92|223 
100 1  Meissner, Pascal,|eauthor. 
245 10 Indoor scene recognition by 3-D object search :|bfor robot
       programming by demonstration /|cPascal Meiner. 
264  1 Cham, Switzerland :|bSpringer,|c2020. 
300    1 online resource (xix, 262 pages) :|billustrations (some 
       color). 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
340    |gpolychrome|2rdacc|0http://rdaregistry.info/termList/
       RDAColourContent/1003 
347    text file|2rdaft|0http://rdaregistry.info/termList/
       fileType/1002 
490 1  Springer tracts in advanced robotics,|x1610-7438 ;|vvolume
       135. 
504    Includes bibliographical references. 
505 0  Introduction -- RelatedWork -- PassiveSceneRecognition -- 
       ActiveSceneRecognition -- Evaluation -- Summary -- 
       Appendix. 
520    This 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. 
588 0  Online resource; title from PDF title page (SpringerLink, 
       viewed October 16, 2019). 
650  0 Robots|xProgramming.|0http://id.loc.gov/authorities/
       subjects/sh85114638 
776 08 |cOriginal|z3030318516|z9783030318512|w(OCoLC)1113882925. 
830  0 Springer tracts in advanced robotics ;|0http://id.loc.gov/
       authorities/names/n2002153858|vv. 135.|x1610-7438. 
990    SpringerLink|bSpringer English/International eBooks 2020 -
       Full Set|c2019-11-08|yAdded to collection 
       springerlink.ebooks2020|5OH1 
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