Multi-Stage Queries and Temporal Scoring in vitrivr

The increase in multimedia data brings many challenges for retrieval systems, not only in terms of storage and processing requirements but also with respect to query formulation and retrieval models. Querying approaches which work well up to a certain size of a multimedia collection might start to decrease in performance when applied to larger volumes of data. In this paper, we present two extensions made to the retrieval model of the open-source content-based multimedia retrieval stack vitrivr which enable a user to formulate more precise queries which can be evaluated in a staged manner, thereby improving the result quality without sacrificing the system's overall flexibility. Our retrieval model has shown its scalability on V3C1, a video collection encompassing approx. 1000 hours of video.