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Super long interval time-lapse image generation for proactive preservation of cultural heritage using crowdsourcing

Super long interval time-lapse image generation for proactive preservation of cultural heritage using crowdsourcing
Super long interval time-lapse image generation for proactive preservation of cultural heritage using crowdsourcing
To establish advanced analytical methods for preserving cultural heritage, this research proposes a method to generate a time-lapse image with a super-long temporal interval. The key issue is to realize an image collection method using crowdsourcing and a method to improve the matching accuracy between images of cultural heritage buildings captured 50 to 100 years ago and current images. As degradation and damage to the appearance of cultural heritage buildings occurs due to ageing, rebuilding, and renovation, image features of the timed images are changed. This decreases the accuracy of the matching process that uses the appearance of patch-region. In addition, we need to give more consideration to incorrect feature correspondence that is prominent in buildings with considerable symmetry. We aim to solve these difficulties by applying an Autoencoder and a guided matching method. Our method involves utilizing the function of crowdsourcing, which can easily obtain the current image captured at the same position and orientation as the past image. We propose this method to address the inability to obtain the correspondence points between two images when observation times are significantly different. © 2019 IEEE.
Advanced Analytics, Big data, Crowdsourcing, Historic preservation, Image matching, Learning systems, Analytical method, Auto encoders, Cultural heritages, Feature correspondence, Position and orientations, Temporal intervals, Time lapse images, Time-lapse, Image enhancement
4632-4637
IEEE
Shishido, H.
266c89c3-848b-4efc-98c5-e1a4dc167fc7
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Kitahara, I.
13b48c1f-8b52-4b65-9f98-e00c2bee22df
Shishido, H.
266c89c3-848b-4efc-98c5-e1a4dc167fc7
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Kitahara, I.
13b48c1f-8b52-4b65-9f98-e00c2bee22df

Shishido, H., Kim, H. and Kitahara, I. (2019) Super long interval time-lapse image generation for proactive preservation of cultural heritage using crowdsourcing. In 2019 IEEE International Conference on Big Data (Big Data). IEEE. pp. 4632-4637 . (doi:10.1109/BigData47090.2019.9006399).

Record type: Conference or Workshop Item (Paper)

Abstract

To establish advanced analytical methods for preserving cultural heritage, this research proposes a method to generate a time-lapse image with a super-long temporal interval. The key issue is to realize an image collection method using crowdsourcing and a method to improve the matching accuracy between images of cultural heritage buildings captured 50 to 100 years ago and current images. As degradation and damage to the appearance of cultural heritage buildings occurs due to ageing, rebuilding, and renovation, image features of the timed images are changed. This decreases the accuracy of the matching process that uses the appearance of patch-region. In addition, we need to give more consideration to incorrect feature correspondence that is prominent in buildings with considerable symmetry. We aim to solve these difficulties by applying an Autoencoder and a guided matching method. Our method involves utilizing the function of crowdsourcing, which can easily obtain the current image captured at the same position and orientation as the past image. We propose this method to address the inability to obtain the correspondence points between two images when observation times are significantly different. © 2019 IEEE.

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More information

Published date: 2019
Additional Information: cited By 0
Venue - Dates: International Conference on Big Data, 2019-05-24
Keywords: Advanced Analytics, Big data, Crowdsourcing, Historic preservation, Image matching, Learning systems, Analytical method, Auto encoders, Cultural heritages, Feature correspondence, Position and orientations, Temporal intervals, Time lapse images, Time-lapse, Image enhancement

Identifiers

Local EPrints ID: 440635
URI: http://eprints.soton.ac.uk/id/eprint/440635
PURE UUID: 03f4e29a-ada1-456b-878f-82a425d107db
ORCID for H. Kim: ORCID iD orcid.org/0000-0003-4907-0491

Catalogue record

Date deposited: 12 May 2020 16:46
Last modified: 13 May 2020 00:59

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Contributors

Author: H. Shishido
Author: H. Kim ORCID iD
Author: I. Kitahara

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