The vitrivr multimedia retrieval stack has been shown to be versatile and effective in many areas and application domains. In this paper, we present vitrivr's new retrieval engine, the vitrivr-engine, a flexible and highly configurable information extraction and query processing solution with support for a broad range of media types.

This tutorial provides an overview of multimedia retrieval in the context of eXtended Reality (XR), including using virtual and augmented/mixed reality as a user interface for multimedia retrieval, as well as multimedia search tasks addressing content needs for the creation of XR experiences.It will discuss the opportunities and limitations of XR-based search, the evaluation of XR-based multimedia retrieval systems, the demonstration of selected research systems, and open research challenges.

The way we create, consume and interact with multimedia content has changed significantly in recent years with the advent of affordable recording devices and easy sharing and access in the form of mobile phones. With the imminent wave of affordable devices that enable mixed reality experiences and the large variety of devices on the market, interaction with multimedia content is expected to continue to evolve rapidly. This will also drastically affect the entire area of multimedia information retrieval in eXtended Reality (XR), for instance by novel ways to express user needs in VR, result presentation that takes the specific capabilities of XR devices into account, and/or result feedback. This tutorial on Multimedia Retrieval in XR discusses and demonstrates existing solutions and highlights key challenges in this evolving field.

Different task interpretations are a highly undesired element in interactive video retrieval evaluations. When a participating team focuses partially on a wrong goal, the evaluation results might become partially misleading. In this paper, we propose a process for refining known-item and open-set type queries, and preparing the assessors that judge the correctness of submissions to open-set queries. Our findings from recent years reveal that a proper methodology can lead to objective query quality improvements and subjective participant satisfaction with query clarity.