Video Keyframe Extraction Algorithm

This study proposes a video shot segmentation algorithm based on window maximum calculation and adaptive thresholding. The algorithm processes video frames by computing window maximum values across sequential frames and applying dynamic threshold adjustment mechanisms. Key implementation aspects include frame difference calculation using color histograms or edge features, sliding window processing for local maxima detection, and adaptive threshold determination based on statistical properties of frame differences. In experimental evaluations, we tested the algorithm on various video genres including action sequences, dialogue scenes, and documentary footage. Comparative analysis with existing methods demonstrates that our approach achieves superior performance in both accuracy (measured through precision-recall metrics) and computational efficiency. The method shows significant potential for practical applications in video indexing, content retrieval, and multimedia analysis systems. The core algorithm workflow involves: 1. Frame feature extraction using HSV color space conversion and histogram comparison 2. Difference curve generation through sliding window maximum operations 3. Adaptive threshold calculation employing statistical measures like mean and standard deviation 4. Shot boundary detection via threshold crossing analysis with temporal constraints