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Texture-based two-stage shot boundary detection in videos

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Two-stage framework improves shot boundary detection accuracy using local quad pattern features, reducing false positives.

The two-stage approach confirms a shot boundary only if both detection stages align, minimizing false positives.
Using local quad pattern histogram features, the method derives key feature vectors for accurate transition detection.
Evaluation on TRECVid 2001 and 2007 datasets shows superior performance over existing shot boundary detection algorithms.
The Euclidean distance method effectively identifies abrupt transitions between consecutive video frames.

Anitha et al. (2025) studied this question.

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