Video Summarization using Color Features and Global Thresholding

Compact representations of video data can enable efficient video browsing. Such representations provide the user with information about the content of the particular sequence being examined. Most of the methods for video summarization relay on complicated clustering algorithms that makes them too computationally complex for real time applications. This paper presents an efficient approach for video summary generation that does not relay on complex clustering algorithms and does not require frame length as a parameter. Our method combines color feature with global thresholding to detect key frame. For each shot a key frame is extracted and similar key frames are eliminated in a simple manner.