Authors:
Xinyun Li
1
;
Ryosuke Furuta
2
;
Go Irie
1
;
Yota Yamamoto
1
and
Yukinobu Taniguchi
1
Affiliations:
1
Department of Information and Computer Technology, Tokyo University of Science, Tokyo, Japan
;
2
Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
Keyword(s):
Indoor Localization, Image Recognition, Similarity Image Search, Scene Text Information.
Abstract:
Due to the increasing complexity of indoor facilities such as shopping malls and train stations, there is a need for a new technology that can find the current location of the user of a smartphone or other device, as such facilities prevent the reception of GPS signals. Although many methods have been proposed for location estimation based on image search, accuracy is unreliable as there are many similar architectural indoors, and there are few features that are unique enough to offer unequivocal localization. Some methods increase the accuracy of location estimation by increasing the number of query images, but this increases the user’s burden of image capture. In this paper, we propose a method for accurately estimating the current indoor location based on question-response interaction from the user, without imposing greater image capture loads. Specifically, the proposal (i) generates questions using object detection and scene text detection, (ii) sequences the questions by minimi
zing conditional entropy, and (iii) filters candidate locations to find the current location based on the user’s response.
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