A visual place recognition method based on semantic instance and bag context

Ruitang Wang; Changshe Ma

doi:10.1117/12.3012485

21 December 2023 A visual place recognition method based on semantic instance and bag context

Ruitang Wang, Changshe Ma

Proceedings Volume 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023); 129702C (2023) https://doi.org/10.1117/12.3012485
Event: Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 2023, Guilin, China

Abstract

Visual place recognition is an essential function for robot system, which can effectively reduce position error via traversing same place. However, a major challenge in this field is to be robust against viewpoint and illumination changes caused by environmental variations. To solve this problem, we propose a novel visual place recognition method in coarse-to-fine manner, which incorporating both high-level semantic feature and bag context information. Firstly, the semantic features of an image are obtained by adopting deep learning network, which converts the image data to the instance representation in more simple way. In coarse stage, we utilize the Bag of word (BoW) model to quantify semantic features by calculating their frequency distribution. In fine stage, we enhance the spatial correlations of semantic objects to further distinguish similar scenes. Through the above two stage, we achieve a robust pipeline of visual place recognition to tackle viewpoint and condition variations. Experimental results on several datasets, including both indoor scenes and outdoor scenes, show that our method achieve good performance, especially for extreme conditions.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ruitang Wang and Changshe Ma "A visual place recognition method based on semantic instance and bag context", Proc. SPIE 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 129702C (21 December 2023); https://doi.org/10.1117/12.3012485

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available