| 000 | 03196nam a22004335i 4500 | ||
|---|---|---|---|
| 988 | _aSpringer_Robotics_2020 | ||
| 999 |
_c117024 _d117024 _x1 |
||
| 001 | 117024 | ||
| 003 | ES-MaUEC | ||
| 005 | 20230110040253.0 | ||
| 006 | a||||fo|||| 00| 0 | ||
| 007 | cr nn nnnaamaa | ||
| 008 | 191011s2020 gw | s |||| 0|eng d | ||
| 020 | _a9783030318529 | ||
| 024 | 7 |
_a10.1007/978-3-030-31852-9 _2doi |
|
| 040 |
_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC |
||
| 050 | 4 |
_aTJ211.45 _b2020 EB |
|
| 100 | 1 |
_aMeißner, Pascal _eautor _9672133 |
|
| 245 | 1 | 0 |
_aIndoor scene recognition by 3-D object search : _bfor robot programming by demonstration _cby Pascal Meißner |
| 250 | _aFirst edition | ||
| 264 | 1 |
_aCham _bSpringer International Publishing _c2020 |
|
| 300 |
_a1 recurso en línea (XIX, 262 páginas) _b116 ilustraciones, 89 ilustraciones a color |
||
| 336 |
_2rdacontent _aTexto _btxt |
||
| 337 |
_2rdamedia _aelectrónico _bc |
||
| 338 |
_2rdacarrier _arecurso electrónico _bcr |
||
| 347 |
_atext file _bPDF |
||
| 490 | 1 |
_aSpringer Tracts in Advanced Robotics _x1610-7438 _v135 |
|
| 490 | 0 | _aTechnologies and Robotics (Springer-42732) | |
| 505 | 0 | _aIntroduction -- RelatedWork -- PassiveSceneRecognition -- ActiveSceneRecognition -- Evaluation -- Summary -- Appendix. . | |
| 520 | 3 | _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. | |
| 650 | 7 |
_2embne _9140106 _aRobots _xProgramación |
|
| 650 | 7 |
_2embne _9668436 _aVisión artificial (Robótica) |
|
| 650 | 7 |
_2embne _aReconocimiento de formas _9152614 |
|
| 776 | 0 | 8 |
_iPrinted edition: _z9783030318512 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030318536 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030318543 |
| 856 | 4 | 0 |
_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-31852-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
| 942 |
_2lcc _cLE |
||
| 998 |
_dz _feng _ggw _h0 _b01/2020 _eel _zSI |
||