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FaceTimeMap: Multi-Level Bitmap Index for Temporal Querying of Faces in Videos
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Author(s): Buddha Shrestha (University of Alabama in Huntsville, Huntsville, USA), Haeyong Chung (University of Alabama in Huntsville, Huntsville, USA)and Ramazan S. Aygün (University of Alabama in Huntsville, Huntsville, USA)
Copyright: 2019
Volume: 10
Issue: 2
Pages: 23
Source title:
International Journal of Multimedia Data Engineering and Management (IJMDEM)
Editor(s)-in-Chief: Chengcui Zhang (University of Alabama at Birmingham, USA)and Shu-Ching Chen (University of Missouri-Kansas City, United States)
DOI: 10.4018/IJMDEM.2019040103
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Abstract
In this article, the authors study bitmap indexing for temporal querying of faces that appear in videos. Since the bitmap index is originally designed to select a set of records that satisfy a value in the domain of the attribute, there is no clear strategy for how to apply it for temporal querying. Accordingly, the authors introduce a multi-level bitmap index that the authors call “FaceTimeMap” for temporal querying of faces in videos. The first level of the FaceTimeMap index is used for determining whether a person appears in a video or not, whereas the second level of the index is used for determining intervals when a person appears. First, the authors analyze the co-appearance query where two or more people appear simultaneously in a video, and then examine next-appearance query where a person appears right after another person. In addition, to consider the gap between the appearance of people, the authors study eventual- and prior-appearance queries. Queries are satisfied by applying bitwise operations on the FaceTimeMap index. The authors provide some performance studies associated with this index.
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