Keynote 2: Similarity Management of Data – the DISA Experience
Pavel Zezula, Masaryk University, Brno
As the current data is weakly structured or unstructured at all, access to objects is only possible through similarity of the object’s salient features or properties. Consequently, similarity approach to searching is increasingly playing more and more important role in development of data processing applications. In the last twenty years, the technology has matured and many centralized, distributed, and even peer-to-peer architectures have been proposed. However, the use of similarity searching in numerous potential applications is still a challenge. In the talk, four research directions in developing similarity search applications at Masaryk University DISA laboratory are to be discussed. First, we concentrate on accelerating large-scale face recognition applications and continue with generic image annotation task for retrieval purposes. In the second half, we focus on data stream processing applications and finish the talk with an ambition topic of content-based retrieval in human motion-capture data. Applications will be illustrated by online prototype implementations.