By the same authors

Image-based Search and Retrieval for Biface Artefacts using Features Capturing Archaeologically Significant Characteristics

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Image-based Search and Retrieval for Biface Artefacts using Features Capturing Archaeologically Significant Characteristics. / Eraminan, M.; Walia, E.; Power, Christopher Douglas; Lewis, A.; Cairns, Paul Antony.

In: Machine Vision and Applications, 02.2017, p. 201-218.

Research output: Contribution to journalArticle

Harvard

Eraminan, M, Walia, E, Power, CD, Lewis, A & Cairns, PA 2017, 'Image-based Search and Retrieval for Biface Artefacts using Features Capturing Archaeologically Significant Characteristics', Machine Vision and Applications, pp. 201-218. https://doi.org/10.1007/s00138-016-0819-x

APA

Eraminan, M., Walia, E., Power, C. D., Lewis, A., & Cairns, P. A. (2017). Image-based Search and Retrieval for Biface Artefacts using Features Capturing Archaeologically Significant Characteristics. Machine Vision and Applications, 201-218. https://doi.org/10.1007/s00138-016-0819-x

Vancouver

Eraminan M, Walia E, Power CD, Lewis A, Cairns PA. Image-based Search and Retrieval for Biface Artefacts using Features Capturing Archaeologically Significant Characteristics. Machine Vision and Applications. 2017 Feb;201-218. https://doi.org/10.1007/s00138-016-0819-x

Author

Eraminan, M. ; Walia, E. ; Power, Christopher Douglas ; Lewis, A. ; Cairns, Paul Antony. / Image-based Search and Retrieval for Biface Artefacts using Features Capturing Archaeologically Significant Characteristics. In: Machine Vision and Applications. 2017 ; pp. 201-218.

Bibtex - Download

@article{7b98fcd0e6174f07bbd8e8884f4f15bb,
title = "Image-based Search and Retrieval for Biface Artefacts using Features Capturing Archaeologically Significant Characteristics",
abstract = "Archaeologists are currently producing huge numbers of digitized photographs to record and preserve artefact finds. These images are used to identify and categorize artefacts and reason about connections between artefacts and perform outreach to the public. However, finding specific types of images within collections remains a major challenge. Often, the metadata associated with images is sparse or is inconsistent. This makes keyword-based exploratory search difficult, leaving researchers to rely on serendipity and slowing down the research process. We present an image-based retrieval system that addresses this problem for biface artefacts. In order to identify artefact characteristics that need to be captured by image features, we conducted a contextual inquiry study with experts in bifaces. We then devised several descriptors for matching images of bifaces with similar artefacts. We evaluated the performance of these descriptors using measures that specifically look at the differences between the sets of images returned by the search system using different descriptors. Through this nuanced approach, we have provided a comprehensive analysis of the strengths and weaknesses of the different descriptors and identified implications for design in the search systems for archaeology.",
author = "M. Eraminan and E. Walia and Power, {Christopher Douglas} and A. Lewis and Cairns, {Paul Antony}",
note = "{\circledC} The Author(s), 2016.",
year = "2017",
month = "2",
doi = "10.1007/s00138-016-0819-x",
language = "English",
pages = "201--218",
journal = "Machine Vision and Applications",
issn = "0932-8092",
publisher = "Springer Verlag",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Image-based Search and Retrieval for Biface Artefacts using Features Capturing Archaeologically Significant Characteristics

AU - Eraminan, M.

AU - Walia, E.

AU - Power, Christopher Douglas

AU - Lewis, A.

AU - Cairns, Paul Antony

N1 - © The Author(s), 2016.

PY - 2017/2

Y1 - 2017/2

N2 - Archaeologists are currently producing huge numbers of digitized photographs to record and preserve artefact finds. These images are used to identify and categorize artefacts and reason about connections between artefacts and perform outreach to the public. However, finding specific types of images within collections remains a major challenge. Often, the metadata associated with images is sparse or is inconsistent. This makes keyword-based exploratory search difficult, leaving researchers to rely on serendipity and slowing down the research process. We present an image-based retrieval system that addresses this problem for biface artefacts. In order to identify artefact characteristics that need to be captured by image features, we conducted a contextual inquiry study with experts in bifaces. We then devised several descriptors for matching images of bifaces with similar artefacts. We evaluated the performance of these descriptors using measures that specifically look at the differences between the sets of images returned by the search system using different descriptors. Through this nuanced approach, we have provided a comprehensive analysis of the strengths and weaknesses of the different descriptors and identified implications for design in the search systems for archaeology.

AB - Archaeologists are currently producing huge numbers of digitized photographs to record and preserve artefact finds. These images are used to identify and categorize artefacts and reason about connections between artefacts and perform outreach to the public. However, finding specific types of images within collections remains a major challenge. Often, the metadata associated with images is sparse or is inconsistent. This makes keyword-based exploratory search difficult, leaving researchers to rely on serendipity and slowing down the research process. We present an image-based retrieval system that addresses this problem for biface artefacts. In order to identify artefact characteristics that need to be captured by image features, we conducted a contextual inquiry study with experts in bifaces. We then devised several descriptors for matching images of bifaces with similar artefacts. We evaluated the performance of these descriptors using measures that specifically look at the differences between the sets of images returned by the search system using different descriptors. Through this nuanced approach, we have provided a comprehensive analysis of the strengths and weaknesses of the different descriptors and identified implications for design in the search systems for archaeology.

UR - http://link.springer.com/article/10.1007/s00138-016-0819-x

U2 - 10.1007/s00138-016-0819-x

DO - 10.1007/s00138-016-0819-x

M3 - Article

SP - 201

EP - 218

JO - Machine Vision and Applications

T2 - Machine Vision and Applications

JF - Machine Vision and Applications

SN - 0932-8092

ER -