Boosting Multimedia Big Data Systems

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Video data is considered as biggest big data. We have witnessed gigantic volume of data generated at a very fast speed in recent years. According to Cisco Systems, video data counts for around 80% of the Internet data in United States. Also, YouTube users upload more than 300 hours’ video clips in every minute. Besides the large volume and velocity, the irregularities and ambiguities (variety property) of the video data make it difficult to compare, understand, and annotate the data using traditional technology and systems. In the proposed research program, our objective is to systematically address the challenges in understanding the complexity of multimedia big data; to handle scalability; to make trade-off between efficiency and accuracy of various solutions; and to design and implement systems to organize, classify, search, and retrieve multimedia contents.