Likelihood Estimation For Slam Using Kinect Device

In the world of robotics, problems of visual SLAM requires an understanding of loop-closure detection and global localization, having said that in order to perform mapping and localization simultaneously we should be able to efficiently recognize an environment that has been previously visited usi...

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Main Authors: Zeeshan, Asim, Sorooshian, Shahryar, Bashir, Ahsan
Format: Article
Language:English
English
Published: IJEAST 2016
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/13912/
http://umpir.ump.edu.my/id/eprint/13912/1/24-29%2CTesma105%2CIJEAST.pdf
http://umpir.ump.edu.my/id/eprint/13912/7/fim-2016-sorooshian-Likelihood%20Estimation%20For%20Slam1.pdf
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author Zeeshan, Asim
Sorooshian, Shahryar
Bashir, Ahsan
author_facet Zeeshan, Asim
Sorooshian, Shahryar
Bashir, Ahsan
author_sort Zeeshan, Asim
building UMP Institutional Repository
collection Online Access
description In the world of robotics, problems of visual SLAM requires an understanding of loop-closure detection and global localization, having said that in order to perform mapping and localization simultaneously we should be able to efficiently recognize an environment that has been previously visited using the current data from our RGBD camera. In this paper we present an online method to recognize and generate information regarding a previously visited place using the visual bag of words model which relies on Bayesian filtering to calculate the probability of loop closure. We would also demonstrate the robustness and effectiveness of our method by real time loop closure detection for an indoor image sequence using Microsoft Kinect camera
first_indexed 2025-11-15T01:55:58Z
format Article
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institution Universiti Malaysia Pahang
institution_category Local University
language English
English
last_indexed 2025-11-15T01:55:58Z
publishDate 2016
publisher IJEAST
recordtype eprints
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spelling ump-139122018-02-28T02:19:54Z http://umpir.ump.edu.my/id/eprint/13912/ Likelihood Estimation For Slam Using Kinect Device Zeeshan, Asim Sorooshian, Shahryar Bashir, Ahsan H Social Sciences (General) In the world of robotics, problems of visual SLAM requires an understanding of loop-closure detection and global localization, having said that in order to perform mapping and localization simultaneously we should be able to efficiently recognize an environment that has been previously visited using the current data from our RGBD camera. In this paper we present an online method to recognize and generate information regarding a previously visited place using the visual bag of words model which relies on Bayesian filtering to calculate the probability of loop closure. We would also demonstrate the robustness and effectiveness of our method by real time loop closure detection for an indoor image sequence using Microsoft Kinect camera IJEAST 2016 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/13912/1/24-29%2CTesma105%2CIJEAST.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/13912/7/fim-2016-sorooshian-Likelihood%20Estimation%20For%20Slam1.pdf Zeeshan, Asim and Sorooshian, Shahryar and Bashir, Ahsan (2016) Likelihood Estimation For Slam Using Kinect Device. International Journal of Engineering Applied Sciences and Technology, 1 (5). pp. 24-29. ISSN 2455-2143. (Published) http://www.ijeast.com/papers/24-29,Tesma105,IJEAST.pdf
spellingShingle H Social Sciences (General)
Zeeshan, Asim
Sorooshian, Shahryar
Bashir, Ahsan
Likelihood Estimation For Slam Using Kinect Device
title Likelihood Estimation For Slam Using Kinect Device
title_full Likelihood Estimation For Slam Using Kinect Device
title_fullStr Likelihood Estimation For Slam Using Kinect Device
title_full_unstemmed Likelihood Estimation For Slam Using Kinect Device
title_short Likelihood Estimation For Slam Using Kinect Device
title_sort likelihood estimation for slam using kinect device
topic H Social Sciences (General)
url http://umpir.ump.edu.my/id/eprint/13912/
http://umpir.ump.edu.my/id/eprint/13912/
http://umpir.ump.edu.my/id/eprint/13912/1/24-29%2CTesma105%2CIJEAST.pdf
http://umpir.ump.edu.my/id/eprint/13912/7/fim-2016-sorooshian-Likelihood%20Estimation%20For%20Slam1.pdf