Large-scale video retrieval via semantic classification

Abstract

Motivated by Google's great success on text document retrieval and recent progresses of semantic video understanding, researchers begin to build new generation of video retrieval systems that are able to support semantic sensitive video retrieval via keywords. Unfortunately, these systems are not able to provide satisfactory results for the masses because of several inter-related challenging problems. We have proposed novel algorithms to resolve some of these problems. Firstly, the salient object based semantic classification algorithm is proposed to extract semantic concepts of video clips. Secondly, the video visualization based interactive retrieval framework is proposed to help users input semantic and visual queries efficiently and effectively. Finally, the concept-oriented skimming algorithm is proposed to help users efficiently check search results.