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Title page for etd-0816105-001043


URN etd-0816105-001043 Statistics This thesis had been viewed 5422 times. Download 1356 times.
Author Liang-wei Hsu
Author's Email Address No Public.
Department Computer Science and Enginerring
Year 2005 Semester 2
Degree Master Type of Document Master's Thesis
Language English Page Count 85
Title Using Artificial Intelligent Approaches to Locating TV Commercial Films
Keyword
  • Commercial Film Locating
  • Commercial Film Detection
  • Artificial Intelligence
  • Artificial Intelligence
  • Commercial Film Detection
  • Commercial Film Locating
  • Abstract  An artificial intelligent (AI) system, integrating ANFIS, ART network and genetic algorithm (GA), is proposed in this thesis to implement the commercial film (CF) detection and locating for the recorded TV programs. According to the types of the recorded TV programs, this content-based detection system can take different strategies to find out the characteristics, which the program content (PC) and CF differ, and then locate CFs. With the probable locations of CFs, an interactive user interface is proposed to enable CF cutting operation. Users can easily find out the precise boundary between CFs and PCs.
    Since commercial films are not related to the program content at all, they are usually not wanted in TV watching. Or users have to trim off the CF parts, and then extract the useful contents from the recorded TV program video for further multimedia editing or authoring. The proposed system uses some AI-based approaches to locate CFs automatically and makes the locating procedure efficient.
     At the end of this thesis, we take some cases to verify the feasibility of this system. Based on the experimental results, the precision rate and recall rate can both reach 90% at least, and the results verify the high usability of the proposed system.
    Advisor Committee
  • Yo-ping Huang - advisor
  • Hsuan-shih Lee - co-chair
  • Wei Yen - co-chair
  • Files indicate access worldwide
    Date of Defense 2005-07-25 Date of Submission 2005-08-16


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