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Contribution Details
Type | Conference or Workshop Paper |
Scope | Discipline-based scholarship |
Published in Proceedings | Yes |
Title | Gesture of Interest: Gesture Search for Multi-Person, Multi-Perspective TV Footage |
Organization Unit | |
Authors |
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Presentation Type | paper |
Item Subtype | Original Work |
Refereed | Yes |
Status | Published in final form |
Language |
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ISBN | 978-1-6654-4220-6 |
Page Range | 1 - 6 |
Event Title | 2021 International Conference on Content-Based Multimedia Indexing (CBMI) |
Event Type | conference |
Event Location | Lille, France |
Event Start Date | July 28 - 2021 |
Event End Date | July 30 - 2021 |
Publisher | IEEE |
Abstract Text | In real-world datasets, specifically in TV recordings, videos are often multi-person and multi-angle, which poses significant challenges for gesture recognition and retrieval. In addition to being of interest to linguists, gesture retrieval is a novel and challenging application for multimedia retrieval. In this paper, we propose a novel method for spatio-temporal gesture retrieval based on visual and pose information which can retrieve similar gestures in multi-person scenes through continuous shots. The attention-aware features, extracted from human pose key-points, together with a sophisticated pre-processing module, alleviate the susceptibility of gesture retrieval to background noise and occlusion. We have evaluated our method on a subset of the NewsScape Dataset. Our experimental results demonstrate the effectiveness of the proposed method in retrieving similar results in occluded scenes as measured by the quality of the top 5 results. |
Related URLs | |
Digital Object Identifier | 10.1109/CBMI50038.2021.9461887 |
Other Identification Number | merlin-id:21246 |
PDF File | Download from ZORA |
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