Improving Face Detection Performance of Compressed MPEG Videos by Using Frame-Independent Scene Change Detection Method

With the spread of computer vision applications, the performance of such applications also became prominent, especially when real-time and near real-time use cases are considered. If not all, many object detection algorithms follow a frame-based search approach, where all frames of the MPEG stream are analyzed sequentially. This drastically increases the computation time and the hardware requirements for such systems. This paper proposes employing a new scene-change detection method to improve object and face detection performance by eliminating the need to analyze every video frame. The method provides a frameindependent approach and does not require decoding and reencoding of MPEG video. The paper also reports the performance test outcomes to exhibit the proposed approach’s value. The findings show that a scene-change detection method enhances efficiency and decreases computational demands. Focusing on frames that show scene changes shows notable advancements in object detection performance.