Mining Entertainment Video Content Structure and Events towards Efficient Access and Scalable Skimming
Umakant Ahirwar, Deepak Bhatnagar · 2013
With the ever-growing digital libraries and video databases, it is increasingly important to understand and mine the knowledge from video database automatically. The media and entertainment industries, including streaming audio and digital TV, present new challenges for managing and accessing large audio-visual collections. In this paper, a shot ontology description based for the football match video. Shot ontology is inferred by shot manipulations that includes shot detection, shot type classification, score board detection and motion statistics .This video content management system provided event feature manipulations at multiple levels: signal, structural, or semantic in order to meet user preferences while striking the overall utility of the video. The experiment results showed that our proposed methodologies could correctly detect interested events, long shots, and close-up shots and also achieved the purpose of video indexing and weaving for what user preferences.