交互式生活日志检索与vitrivr

Silvan Heller, Mahnaz Parian, Ralph Gasser, Loris Sauter, H. Schuldt
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引用次数: 27

摘要

我们日常生活中收集的数据的种类和数量对多媒体检索提出了独特的挑战。在Lifelog搜索挑战(LSC)中,多媒体检索系统在基于包含结构化、半结构化和非结构化数据提示的描述来查找事件方面展开竞争。在本文中,我们介绍了多媒体检索系统vitrivr,重点介绍了基于新数据集所做的更改和补充,以及我们在LSC 2019上的成功参与。具体来说,我们展示了如何在不牺牲效率的情况下以不同的方式使用新数据集进行检索,描述了两个最近增加的内容,时间评分和分阶段查询,并讨论了用于丰富数据集的深度学习方法。
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Interactive Lifelog Retrieval with vitrivr
The variety and amount of data being collected in our everyday life poses unique challenges for multimedia retrieval. In the Lifelog Search Challenge (LSC), multimedia retrieval systems compete in finding events based on descriptions containing hints about structured, semi-structured an unstructured data. In this paper, we present the multimedia retrieval system vitrivr with a focus on the changes and additions made based on the new dataset, and our successful participation at LSC 2019. Specifically, we show how the new dataset can be used for retrieval in different modalities without sacrificing efficiency, describe two recent additions, temporal scoring and staged querying, and discuss the deep learning methods used to enrich the dataset.
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FIRST - Flexible Interactive Retrieval SysTem for Visual Lifelog Exploration at LSC 2020 Voxento: A Prototype Voice-controlled Interactive Search Engine for Lifelogs Myscéal: An Experimental Interactive Lifelog Retrieval System for LSC'20 LifeSeeker 2.0: Interactive Lifelog Search Engine at LSC 2020 BIDAL-HCMUS@LSC2020: An Interactive Multimodal Lifelog Retrieval with Query-to-Sample Attention-based Search Engine
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