Combining Boolean and Multimedia Retrieval in vitrivr for large-scale Video Search
This paper presents the most recent additions to the vitrivr multimedia retrieval stack made in preparation for the participation to the 9th Video Browser Showdown (VBS) in 2020. In addition to refining existing functionality and adding support for classical Boolean queries and metadata filters, we also completely replaced our storage engine ADAMpro by a new database called Cottontail DB. Furthermore, we have added support for scoring based on the temporal ordering of multiple video segments with respect to a query formulated by the user. Finally, we have also added a new object detection module based on Faster-RCNN and use the generated features for object instance search.