Shot Boundary Detection and Low-Level Feature Extraction Experiments for TRECVID 2005

1. Briefly, what approach or combination of approaches did you test in each of your submitted runs? bs-1: Compressed domain approach, which corresponds to the best options in TRECVID 2004 with newly introduced luminance adaptive threshold. bs-2: Compressed domain approach with newly introduced luminance adaptive threshold and image cropping. bs-3: Compressed domain approach with parameter optimization in TRECVID 2004. bs-4: Compressed domain approach with newly introduced image cropping. bs-5: Compressed domain approach, which corresponds to the best options in TRECVID 2004 without any optimization and extension. bs-6: Uncompressed domain approach with an abrupt cut detector based on data fusion technique with SVM trained with TV2004 ref. But short gradual cuts are not trained. Novel feature derived from image synthesis parameters are introduced. bs-7: Uncompressed domain approach with the same technique of bs-6. Trained data is also TV2004 ref. But Short gradual cuts are trained. bs-8: Variant of bs-7. Abrupt cuts are trained from TV2004 ref. Short gradual cuts are trained from the subset of 2005 develop. bs-9: Result of bs-1's grad and that of bs-7’s cut are merged. bs-10: Result of bs-1's grad and that of bs-8's cut are merged.

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