Real Time Key Frame Extraction Through Parallel Computation of Entropy Difference

Abstract

The advancement of image processing in the field of Artificial Intelligence has created various research prospects in the area of object detection, pattern recognition etc. Capturing real time video stream for multiple cameras within a region of interest has become a common phenomenon for an Intelligent Situation Awareness System. Video processing is an important application which is rapidly developing nowadays as an area of extensive research. Content retrieval as well as information collection from a video requires both syntactic and semantic analysis. For a large video data, some set of frames are used to represent the video content. These are identified as key frames. Several algorithms have been defined to extract key frames from a stored video file. The existing algorithms that have been defined for key frame extraction are based on sequential mode. This paper looks into the extraction of key frames for any real time video stream. The experimental results show that there is an effective reduction in the execution time to a huge extent in the case of distributed processing as compared to the sequential processing of frames. In this paper, we propose a distributed framework to regulate the speed of key frame generation for heterogeneous speed of incoming video.