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Multimodal Video Retrieval with the 2017 IMOTION System

Rossetto, Luca and Giangreco, Ivan and Tanase, Claudiu and Schuldt, Heiko. (2017) Multimodal Video Retrieval with the 2017 IMOTION System. In: Proceedings of the 2017 ACM International Conference on Multimedia Retrieval (ICMR 2017). pp. 457-460.

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Abstract

The IMOTION system is a multimodal content-based video search and browsing application offering a rich set of query modes on the basis of a broad range of different features. It is able to scale with the size of the collection due to its underlying flexible polystore called ADAMpro and its very effective retrieval engine Cineast, optimized for multi-feature fusion. IMOTION is simultaneously geared towards precision-focused searches, i.e., known-item search with image or text queries, and recall-focused, exploratory searches. In this demo, we will present the 2017 IMOTION system deployed on the IACC.3 collection consisting of 600 hours of Internet Archive video, which was also used in the TRECVID 2016 Ad-Hoc Video Search and in the 2017 Video Browser Showdown (VBS) challenge in which IMOTION ranked first. Conference attendees will have the chance to interact with the 2017 IMOTION system and quickly solve various retrieval tasks.
Faculties and Departments:05 Faculty of Science > Departement Mathematik und Informatik > Informatik > Datenbanken (Schuldt)
UniBasel Contributors:Schuldt, Heiko and Rossetto, Luca and Giangreco, Ivan and Tanase, Claudiu-Ioan
Item Type:Conference or Workshop Item, refereed
Conference or workshop item Subtype:Conference Paper
Publisher:ACM
ISBN:978-1-4503-4701-3
Note:Publication type according to Uni Basel Research Database: Conference paper
Language:English
Identification Number:
Last Modified:14 Mar 2019 06:31
Deposited On:16 Mar 2018 12:12

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