Novice-Friendly Video Retrieval in Mixed Reality with Vitrivr-VR
Multimedia data, such as images and videos, continue to be recorded and created in ever increasing quantities. Multimedia collections on social media, but also private collections of personal vacation and home videos are being collected at a higher rate than ever. This rapid growth makes it difficult, and in many cases impossible, to effectively use this kind of data without the use of automated analysis methods. While many methods have been developed to automate the analysis of multimedia data, users are unable to access the information extracted through this analysis without appropriate interfaces. Although purpose-built user interfaces are important even for use by trained experts, they are essential in facilitating the interaction with large multimedia data collections for laypersons and novices. In this paper, we describe a new and improved version of vitrivr-VR, a prototype multimedia analytics system built for immersive interfaces, in the form in which it will participate in the Video Retrieval for Beginners (VR4B) evaluation campaign. vitrivr-VR aims to improve the video browsing experience for novices through the additional affordances provided by immersive interfaces. We describe the current state of the system with a focus on features and adjustments made to support accessibility of large scale multimedia analytics for novices.