Image-based search and retrieval for biface artefacts using features capturing archaeologically significant characteristics
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- 作者：Mark Eramian ; Ekta Walia ; Christopher Power ; Paul Cairns…
- 关键词：Image retrieval ; Image ; based search ; Biface ; Archaeology ; Artifacts ; Flint
- 刊名：Machine Vision and Applications
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：28
- 期：1-2
- 页码：201-218
- 全文大小：2152KB
- 刊物类别：Computer Science
- 刊物主题：Pattern Recognition; Image Processing and Computer Vision; Communications Engineering, Networks;
- 出版者：Springer Berlin Heidelberg
- ISSN：1432-1769
- 卷排序：28
文摘
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.