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.
Primary Language | English |
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Subjects | Computer Software, Software Engineering (Other) |
Journal Section | Araştırma Articlessi |
Authors | |
Early Pub Date | October 10, 2025 |
Publication Date | October 15, 2025 |
Submission Date | November 2, 2024 |
Acceptance Date | November 28, 2024 |
Published in Issue | Year 2025 Volume: 13 Issue: 3 |
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