Dimensionality reduction through visual data resampling for low-storage loop-closure detection-Reference-Cited by-同舟云学术

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Dimensionality reduction through visual data resampling for low-storage loop-closure detection

Published:2022-06-21 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Imaging Systems and Techniques (IST)
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Author:

Tsintotas Konstantinos A.¹,An Shan²,Papapetros Ioannis Tsampikos¹,Konstantinidis Fotios K.¹,Sirakoulis Georgios Ch.³,Gasteratos Antonios¹

Affiliation:

1. Democritus University of Thrace,Department of Production and Management Engineering,Xanthi,Greece,GR-671 32

2. JD.com,AR/VR department,Beijing,China,100191

3. Democritus University of Thrace,Department of Electrical and Computer Engineering,Xanthi,GR,Greece,67 100

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9827659/9827662/09827748.pdf?arnumber=9827748

Reference68 articles.

1. Fast relocalisation and loop closing in keyframe-based SLAM

2. Video Google: a text retrieval approach to object matching in videos

3. KAZE Features

4. BRISK: Binary Robust invariant scalable keypoints

5. ORB: An efficient alternative to SIFT or SURF

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