Retrieval of Structured and Unstructured Data with vitrivr

Luca Rossetto, Ralph Gasser, Silvan Heller, Mahnaz Amiri Parian, Heiko Schuldt
In Proceedings
Appears in
Proceedings of the International Conference on Multimedia Retrieval (ICMR)
Ottawa, ON, Canada

With the increase in sensory capability of mobile devices, the data that can be generated and used in a lifelogging context gets increasingly diverse. Such data is special in the context of multimedia, not only because of its close personal relationship with its originator, but also because of its diverse multimodality and its composition from structured, semi-structured, and unstructured data. This diversity poses retrieval challenges that are unique to lifelog data but which also have implications for retrieval activity in other multimedia domains.

In this paper, we present the extensions made to the vitrivr open-source multimedia retrieval stack, in order to address some of these unique lifelogging challenges. For the participation to the 2019 Lifelog Search Challenge (LSC), we have extended vitrivr with the capability to process Boolean query expressions alongside content-based query descriptions in order to leverage the structural diversity inherent to lifelog data.

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