Ten Research Questions for Scalable Multimedia Analytics

Abstract

Abstract. The scale and complexity of multimedia collections is ever increasing, as is the desire to harvest useful insight from the collections. To optimally support the complex quest for insight, multimedia analytics has emerged as a new research area that combines concepts and techniques from multimedia analysis and visual analytics into a single framework. State of the art multimedia analytics solutions are highly interactive and give users freedom in how they perform their analytics task, but they do not scale well. State of the art scalable database management solutions, on the other hand, are not yet designed for multimedia analytics workloads. In this position paper we therefore argue the need for research on scalable multimedia analytics, a new research area built on the three pillars of visual analytics, multimedia analysis and database management. We propose a specific goal for scalable multimedia analytics and present several important research questions that we believe must be addressed in order to achieve that goal.

Interactive Learning for Multimedia at Large

“…As the general public has been given tools for unprecedented media production, storage and sharing, media generation and consumption have increased drastically in recent years. Furthermore, upcoming multimedia applications in countless domains-from smart urban spaces and business intelligence to health and wellness, lifelogging, and entertainmentincreasingly require joint modelling of multiple modalities [20,47]. Finally, users expect to be able to work very efficiently with large-scale collections, even with the limited computing resources they have at their immediate disposal.…”