Developing a robust framework to reduce the size of a recorded video surveillance systems - Alamin, Sabri Mohammed; Khalifa, Othman Omran (SERSC: Science & Engineering Research Support Society, 2018)
Most of the video surveillance strategies take a significant amount of space for storage as surveillance camera's unexceptionally recorded everything during camera – on time. Whereby, it leads to consuming the storage capacity of the device of the system. In fact, many algorithms have been proposed solving in the dilemma to object recognition and compress the video to reduce the size whenever it save's data. Nevertheless, the technology deprived efficient methods to reducing the storage of space for consummation. The Idea of this paper is to propose a framework on how to possibly can be reduce the size of a recorded video of the surveillance system via recording only the part of the video that contains the motion, and ignore the other parts based on the motion detection. The result shows that the framework give an outstanding results on the uncompressed surveillance video recorded from a single fixed camera. The proposed framework enables to save 30% more of playback time and can provide more than 50% of storage of space saving.