Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/71242
Title: Video indexing using face appearance and shot transition detection
Authors: Cazzato, Dario
Leo, Marco
Carcagni, Pierluigi
DIstante, Cosimo
Lorenzo-Navarro, Javier 
Voos, Holger
UNESCO Clasification: 120304 Inteligencia artificial
Keywords: Assistive technology
Face analysis
Video indexing
Issue Date: 2019
Journal: Proceedings - 2019 International Conference On Computer Vision Workshop, Iccvw 2019
Conference: 17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019 
Abstract: The possibility to automatically index human faces in videos could lead to a wide range of applications such as automatic video content analysis, data mining, on-demand streaming, etc. Most relevant works in the literature gather full indexing of videos in real scenarios by exploiting additional media features (e.g. audio and text) that are fused with facial appearance information to make the whole frameworks accurate and robust. Anyway, there exist some application contexts where multimedia data are either not available or reliable and for which available solutions are not well suited. This paper tries to explore this challenging research path by introducing a new fully computer vision based video indexing pipeline. The system has been validated and tested in two different typical scenarios where no-multimedia data could be exploited: broadcasted political video documentaries and healthcare therapies sessions about non-verbal skills.
URI: http://hdl.handle.net/10553/71242
ISBN: 978-1-7281-5024-6
ISSN: 2473-9936
DOI: 10.1109/ICCVW.2019.00319
Source: Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019, p. 2611-2618
Appears in Collections:Actas de congresos
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