Paper Info
Title
A Holistic Visual Place Recognition Approach Using Lightweight CNNs for Significant ViewPoint and Appearance Changes
Abstract
This article presents a lightweight visual place recognition approach, capable of achieving high performance with low computational cost, and feasible for mobile robotics under significant viewpoint and appearance changes. Results on several benchmark datasets confirm an average boost of 13% in accuracy, and 12 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</italic> average speedup relative to state-of-the-art methods.
Year
DOI
Venue
2020
10.1109/TRO.2019.2956352
IEEE Transactions on Robotics
Keywords
DocType
Volume
Convolutional neural network (CNN),feature encoding,robot localization,vector of locally aggregated descriptors (VLADs),visual place recognition (VPR)
Journal
36
Issue
ISSN
Citations 
2
1552-3098
3
PageRank 
References 
Authors
0.38
0
5
Name
Order
Citations
PageRank
Ahmad Khaliq130.38
Shoaib Ehsan211024.43
Zetao Chen3927.78
Michael Milford4122184.09
Klaus D. McDonald-Maier532754.43