Active sensor planning for multiview vision tasks

Vision sensors have limited fields of views and can only "see" a portion of a scene from a single viewpoint. To make the entire object visible, the sensor has to be moved from one place to another around the object to observe all features of interest, which brings a multiview vision task t...

Full description

Saved in:
Bibliographic Details
Main Authors: Chen, S., Li, Y.F., Zhang, J.
Format: Book
Language:English
Published: Springer 2017
Subjects:
Online Access:http://repository.vnu.edu.vn/handle/VNU_123/23906
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Vietnam National University, Hanoi
Language: English
id oai:112.137.131.14:VNU_123-23906
record_format dspace
spelling oai:112.137.131.14:VNU_123-239062020-07-06T08:38:42Z Active sensor planning for multiview vision tasks Chen, S. Li, Y.F. Zhang, J. Engineering ; Detectors -- Calibration ; Multisensor data fusion 621.3 Vision sensors have limited fields of views and can only "see" a portion of a scene from a single viewpoint. To make the entire object visible, the sensor has to be moved from one place to another around the object to observe all features of interest, which brings a multiview vision task that has to be solved by means of active perception. The sensor planning presented in this book describes some effective strategies to generate a sequence of viewing poses and sensor settings for optimally completing a perception task. Several methods are proposed to solve the problems in both model-based and nonmodel-based vision tasks. For model-based applications, the method involves determination of the optimal sensor placements and a shortest path through these viewpoints for automatic generation of a perception plan. For nonmodel-based applications, the method involves determination of the best next view and sensor settings, to incrementally acquire the object information and to find geometrical cues to predict the unknown portion of an object or environment. The ten chapters in Active Vision Planning draw on recent work in robot vision over ten years, particularly in the use of new concepts of active sensing, reconfiguration, recalibration, sensor modeling, sensing constraints, sensing evaluation, viewpoint decision, sensor placement graph, model based planning, path planning, planning for robot in unknown environment, dynamic 3D construction, surface prediction, etc. Implementation examples are also provided with theoretical methods for testing in a real robot system. With these optimal sensor planning strategies, this book will give the robot vision system the adaptability needed in many practical applications. 2017-04-04T02:26:08Z 2017-04-04T02:26:08Z 2008 Book 978354077718 http://repository.vnu.edu.vn/handle/VNU_123/23906 en 270 p. application/pdf Springer
institution Vietnam National University, Hanoi
building VNU Library & Information Center
country Vietnam
collection VNU Digital Repository
language English
topic Engineering ; Detectors -- Calibration ; Multisensor data fusion
621.3
spellingShingle Engineering ; Detectors -- Calibration ; Multisensor data fusion
621.3
Chen, S.
Li, Y.F.
Zhang, J.
Active sensor planning for multiview vision tasks
description Vision sensors have limited fields of views and can only "see" a portion of a scene from a single viewpoint. To make the entire object visible, the sensor has to be moved from one place to another around the object to observe all features of interest, which brings a multiview vision task that has to be solved by means of active perception. The sensor planning presented in this book describes some effective strategies to generate a sequence of viewing poses and sensor settings for optimally completing a perception task. Several methods are proposed to solve the problems in both model-based and nonmodel-based vision tasks. For model-based applications, the method involves determination of the optimal sensor placements and a shortest path through these viewpoints for automatic generation of a perception plan. For nonmodel-based applications, the method involves determination of the best next view and sensor settings, to incrementally acquire the object information and to find geometrical cues to predict the unknown portion of an object or environment. The ten chapters in Active Vision Planning draw on recent work in robot vision over ten years, particularly in the use of new concepts of active sensing, reconfiguration, recalibration, sensor modeling, sensing constraints, sensing evaluation, viewpoint decision, sensor placement graph, model based planning, path planning, planning for robot in unknown environment, dynamic 3D construction, surface prediction, etc. Implementation examples are also provided with theoretical methods for testing in a real robot system. With these optimal sensor planning strategies, this book will give the robot vision system the adaptability needed in many practical applications.
format Book
author Chen, S.
Li, Y.F.
Zhang, J.
author_facet Chen, S.
Li, Y.F.
Zhang, J.
author_sort Chen, S.
title Active sensor planning for multiview vision tasks
title_short Active sensor planning for multiview vision tasks
title_full Active sensor planning for multiview vision tasks
title_fullStr Active sensor planning for multiview vision tasks
title_full_unstemmed Active sensor planning for multiview vision tasks
title_sort active sensor planning for multiview vision tasks
publisher Springer
publishDate 2017
url http://repository.vnu.edu.vn/handle/VNU_123/23906
_version_ 1680967204744462336