Shot Boundary Determination on MPEC Compressed Domain and Story Segmentation Experiments for TRECVID 2003

1. Briefly, what approach or combination of approaches did you test in each of your submitted runs? 1_kddi_ss_base1_5: “Baseline” method based on SVM, which discriminates shots that contain story boundaries. 1_kddi_ss_c+k1_4: Baseline + section-specialized segmentation (SS-S). 1_kddi_ss_all1_3: Baseline + SS-S + anchor shot segmentation (ASS) based on audio classification results 1_kddi_ss_all1_pfil_1: Baseline + SS-S + ASS and post-filtering (PF) based on audio classification results 1_kddi_ss_all2_pfil_2: Extended baseline + SS-S + ASS + PF based on audio classification results. 1_kddi_ss_all1nsp07_pfil_6: Baseline + SS-S + ASS + PF by HMM-based non-speech detection. 1_kddi_ss_all2nsp07_pfil_7: Extended baseline + SSS + ASS + PF by HMM-based non-speech detection. 2_kddi_ss2_all1_pfil_8: Baseline + SS-S + ASS and PF based on "speech segment" information from LIMSI ASR results[1]. 2_kddi_ss2_all2_pfil_9: Extended baseline + SS-S + ASS and PF based on "speech segment" information from LIMSI ASR results. 3_kddi_ss3_10: Naive TextTiling based story segmentation based on LIMSI ASR data.

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