Video Object Mining: Issues and Perspectives

Today, video is becoming one of the primary sources of information. Current video mining systems face the problem of the semantic gap (i.e., the difference between the semantic meaning of video contents and the digital information encoded within the video files). This gap can be bridged by relying on the real objects present in videos because of the semantic meaning of objects. But video object mining needs some semantics, both in the object extraction step and in the object mining step. We think that the introduction of semantics during these steps can be ensured by user interaction. We then propose a generic framework to deal with video object mining.