Dr. Christian Beecks | 24.11.2015 | 16:00 Uhr | E.2.42
With the advent of social networks and the advancement of powerful internet-enabled mobile devices, millions of users are able to easily generate, process, and share multimedia data at billion-scale every single day. The resulting multitude and versatility of multimedia data made available in the Internet challenge todays’ data management and analysis algorithms. In many research and application areas including information retrieval, data mining, and computer vision, users are no longer satisfied with keyword-based access but want to search, browse, explore, and analyze multimedia data according to content-based characteristics. One fundamental operation underlying many data analysis algorithms is similarity search which aims at retrieving the most similar multimedia objects with respect to a query. In order to carry out similarity search for query-like multimedia objects, the way of modeling similarity is of major significance due to its impact on efficiency and effectiveness.
In this talk, I will present my ongoing research in this fascinating field and highlight future research directions. More specifically, I will show how to approach similarity between multimedia data objects by means of gradient-based signatures in order to facilitate data analysis with high efficiency and efficacy.
Christian Beecks is a postdoctoral researcher in the data management and data exploration group at RWTH Aachen University, Germany. His research interests include efficient and adaptive multimedia data analysis, distance-based multimedia indexing and query processing, and real-time data management.