Video Shot Boundary Detection

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Hosseini, Mehdi | 2016

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 49102 (05)
University: Sharif University of Technology
Department: Electrical Engineering
Advisor(s): Sharifkhani, Mohammad
Abstract:
Digital video is one of the biggest part of digital data. The first step of digital video analytics is shot boundary detection. We used overlapped partitioning beside color histogram in uncompressed data and macroblock type prediction in compressed data as feature and supervised classifiers for decision making. Tests on TRECVID 2006 shows 8.9% improvement of F-measure in uncompressed video and 5.3% in h.264 bitstream. Supplementary test is done on IRIB dataset which shows 5.7% improvement of F-measure in uncompressed and 3.2% in H.264. H.264 based algorithm is almost 7 times faster in comparison to the algorithm that includes decoding
Keywords:
Shot Boundary Detection ; H.264 Video Codec ; Support Vector Machine (SVM)Classifier ; Moving Picture Expert Group (MPEG)Standard ; Video Compression ; Digital Video Analytics

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