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ACM Multimedia 2009 Grand Challenges



At Google Research we interact with the academic research community closely through various programs like Research Awards, Visiting Faculty Program, and by active participation in various conferences. Dealing with large quantities of data gives us some unique challenges and perspectives on various problems. In many cases entirely new problem classes begin to emerge. These problems often have not received attention from a broad part of the research community. In an effort to bridge this gap for multimedia problems, we participated in setting Grand Challenges for this year's ACM Multimedia Conference. We proposed "Robust, As-Accurate-As-Human Genre Classification for Video" as a challenge.

The majority of research in video analysis today focuses on surveillance video. While this is critical for a lot of security applications, it is incomplete in describing challenges that come up when we tackle a video retrieval and discovery application like YouTube. Analysis work beyond surveillance is often limited to specific categories like News and Sports that have well defined structures that the solution methods can explicitly work with. Our challenge aims to encourage more work in the area of semantic understanding of a broad variety of videos. Genre classification is a problem thats representative of some of the challenges that stem from the sheer diversity that can exist across video categories. The challenge will encourage new methods to solve these problems, as well as attempts at standardizing datasets to represent this problem. With internet video gaining popularity in an astounding magnitude, we believe this challenge will steer the multimedia research community towards challenges posed by the magnitude and variety of this new problem area.

We are grateful to Mor Naaman (Rutgers University) and Tat-Seng Chua (National University of Singapore) for organizing this industry challenge track at ACM Multimedia and inviting us to be a part of it.

Details of our challenge can be found here.
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