Extracting Semantics From Multimedia Content: Challenges and Solutions

Multimedia content accounts for over 60% of traffic in the current internet. With many users willing to spend their leisure time watching videos on YouTube or browsing photos through Flickr, sifting through large multimedia collections for useful information, especially those outside of the open web, is still an open problem. The lack of effective indexes to describe the content of multimedia data is a main hurdle to multimedia search, and extracting semantics from multimedia content is the bottleneck for multimedia indexing. In this chapter, the authors present a review on extracting semantics from a large amount of multimedia data as a statistical learning problem.