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http://dx.doi.org/10.3745/KIPSTB.2003.10B.6.611

Shot Boundary Detection of Video Data Based on Fuzzy Inference  

Jang, Seok-Woo (한국건설기술연구원 건설경영정보연구부 건설CALS연구센터)
Publication Information
The KIPS Transactions:PartB / v.10B, no.6, 2003 , pp. 611-618 More about this Journal
Abstract
In this paper, we describe a fuzzy inference approach for detecting and classifying shot transitions in video sequences. Our approach basically extends FAM (Fuzzy Associative Memory) to detect and classify shot transitions, including cuts, fades and dissolves. We consider a set of feature values that characterize differences between two consecutive frames as input fuzzy sets, and the types of shot transitions as output fuzzy sets. The inference system proposed in this paper is mainly composed of a learning phase and an inferring phase. In the learning phase, the system initializes its basic structure by determining fuzzy membership functions and constructs fuzzy rules. In the inferring phase, the system conducts actual inference using the constructed fuzzy rules. In order to verify the performance of the proposed shot transition detection method experiments have been carried out with a video database that includes news, movies, advertisements, documentaries and music videos.
Keywords
Shot boundary detection; Feature extraction; Video data; Fuzzy inference;
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