Interactive Lifelog Retrieval with vitrivr

Authors
Silvan Heller, Mahnaz Amiri Parian, Ralph Gasser, Loris Sauter, Heiko Schuldt
Type
In Proceedings
Date
2020/10
Appears in
Proceedings of the Third Annual Workshop on Lifelog Search Challenge (LSC 2020)
Location
Dublin, Ireland (held virtually)
Pages
1-6
Abstract

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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