Augmented keyframe
In surveillance applications, keyframes are usually used to summarize important video contents. However, most traditional keyframe extraction approaches just select some video frames from the input video, while the information in these selected video frames are insufficient and cannot let the users perceive the events happened in the original video easily. In this paper, we propose a novel keyframe generating technique to condense the contents of a surveillance video clip captured by a static camera into a still picture (augmented keyframe). The augmented keyframe is a more meaningful keyframe augmented with representative objects, important contents (human faces, license plate, etc.), motion status (represented as icons) and some marks of the moving objects in a still picture. This new technique consists of two major phases: content extraction and content synthesis. Some testing results of the proposed augmented keyframe are also presented and compared with results obtained by the traditional keyframe approach.
keyframe surveillance video content extraction content synthesis video abstraction video summarization object tracking motion analysis