Poster for the WCE’13 paper that was awarded “Best Student Paper” award,
INTRODUCTION:
Videos, especially the compressed ones, became a major part of our daily life. With the amount of videos growing exponentially, Scientists are being pushed to develop robust tools that could efficiently index and retrieve videos in a way similar to human perception of similarity.
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PROBLEM
§Manual annotation is a hard work and annotations are not always available for utilization.
§We need more smarter tagging process for videos.
§With the increasing of compressed videos, more efficient techniques are required to work directly on compressed files, without need for decompression.
AIM
Our aim is to build a framework that will operate on compressed videos (utilizing the DC-images sequence),
CONCLUSION
•DC-IMAGE is suitable for cheaper computations and could be used as basic building block for real-time processing.
•Local features proved to be effective on DC-image, after our introduced modification.
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