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Indoor Scene Recognition By 3d Object Search For Robot Programming By Demonstration 1st Ed 2020 Pascal Meiner

  • SKU: BELL-10800738
Indoor Scene Recognition By 3d Object Search For Robot Programming By Demonstration 1st Ed 2020 Pascal Meiner
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Indoor Scene Recognition By 3d Object Search For Robot Programming By Demonstration 1st Ed 2020 Pascal Meiner instant download after payment.

Publisher: Springer International Publishing
File Extension: PDF
File size: 10.19 MB
Author: Pascal Meißner
ISBN: 9783030318512, 9783030318529, 3030318516, 3030318524
Language: English
Year: 2020
Edition: 1st ed. 2020

Product desciption

Indoor Scene Recognition By 3d Object Search For Robot Programming By Demonstration 1st Ed 2020 Pascal Meiner by Pascal Meißner 9783030318512, 9783030318529, 3030318516, 3030318524 instant download after payment.

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.

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