Multimodal Video Retrieval with the 2017 IMOTION System

Rossetto, Luca; Giangreco, Ivan; Tanase, Claudiu; Schuldt, Heiko

doi:10.1145/3078971.3079012

Cited by 8 publications

(3 citation statements)

References 12 publications

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“…Next, the framework provides the journalist an interactive way to explore retrieved footage, either by updating queries or by altering control sliders for relevant concepts. Several multimodal video retrieval systems have previously been proposed [2,4,9]. In these systems the interactive component is Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page.…”

Section: Introductionmentioning

confidence: 99%

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Interactive Exploration of Journalistic Video Footage through Multimodal Semantic Matching

Ibrahimi

Chen

Arya

et al. 2019

Proceedings of the 27th ACM International Conference on Multimedia

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This demo presents a system for journalists to explore video footage for broadcasts. Daily news broadcasts contain multiple news items that consist of many video shots and searching for relevant footage is a labor intensive task. Without the need for annotated video shots, our system extracts semantics from footage and automatically matches these semantics to query terms from the journalist. The journalist can then indicate which aspects of the query term need to be emphasized, e.g. the title or its thematic meaning. The goal of this system is to support the journalists in their search process by encouraging interaction and exploration with the system. CCS CONCEPTS• Information systems → Search interfaces; • Human-centered computing → Systems and tools for interaction design.

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Section: Introductionmentioning

confidence: 99%

“…either missing [2] or in the form of relevance feedback [4] to improve future model results. In [9], the user is able to refine results to indicate the importance of different features. Contrarily, our system places exploration as its central component.…”

Section: Introductionmentioning

confidence: 99%

Interactive Exploration of Journalistic Video Footage through Multimodal Semantic Matching

Ibrahimi

Chen

Arya

et al. 2019

Proceedings of the 27th ACM International Conference on Multimedia

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“…In this paper we present the current iteration of vitrivr [6], an open-source content-based multimedia retrieval stack. The vitrivr stack is the continuation of the IMOTION system [3,5,7,8] which participated in previous iterations of the Video Browser Showdown [1]. Despite offering some new functionality, the primary focus for this years participation lies in the simplification and generalization of the retrieval stack in order to make it easier to adapt, deploy, and use by both experts and laymen.…”

Section: Introductionmentioning

confidence: 99%

Competitive Video Retrieval with vitrivr

Rossetto

Giangreco

Gasser

et al. 2018

MultiMedia Modeling

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This paper presents the competitive video retrieval capabilities of vitrivr. The vitrivr stack is the continuation of the IMOTION system which participated to the Video Browser Showdown competitions since 2015. The primary focus of vitrivr and its participation in this competition is to simplify and generalize the system's individual components, making them easier to deploy and use. The entire vitrivr stack is made available as open source software.

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