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Semantic Sketch-Based Video Retrieval with Autocompletion

Tănase, Claudiu and Giangreco, Ivan and Rossetto, Luca and Schuldt, Heiko and Seddati, Omar and Dupont, Stéphane and Altiok, Ozan Can and Sezgin, Metin. (2016) Semantic Sketch-Based Video Retrieval with Autocompletion. In: Proceedings of the 21st ACM International Conference on Intelligent User Interfaces (IUI’16). New York, NY , pp. 97-101.

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Official URL: http://edoc.unibas.ch/51979/

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Abstract

The IMOTION system is a content-based video search engine that provides fast and intuitive known item search in large video collections. User interaction consists mainly of sketching, which the system recognizes in real-time and makes suggestions based on both visual appearance of the sketch (what does the sketch look like in terms of colors, edge distribution, etc.) and semantic content (what object is the user sketching). The latter is enabled by a predictive sketch-based UI that identifies likely candidates for the sketched object via state-of-the-art sketch recognition techniques and offers on-screen completion suggestions. In this demo, we show how the sketch-based video retrieval of the IMOTION system is used in a collection of roughly 30,000 video shots. The system indexes collection data with over 30 visual features describing color, edge, motion, and semantic information. Resulting feature data is stored in ADAM, an efficient database system optimized for fast retrieval.
Faculties and Departments:05 Faculty of Science > Departement Mathematik und Informatik > Informatik > Datenbanken (Schuldt)
UniBasel Contributors:Schuldt, Heiko and Tanase, Claudiu-Ioan and Rossetto, Luca and Giangreco, Ivan
Item Type:Conference or Workshop Item, refereed
Conference or workshop item Subtype:Conference Paper
Publisher:ACM
ISBN:978-1-4503-4140-0
Note:Publication type according to Uni Basel Research Database: Conference paper
Language:English
Identification Number:
Last Modified:07 May 2018 08:37
Deposited On:28 Nov 2017 11:11

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