Abstract
Video data consists of a sequence of shots. Over the past several years, substantial progress has been made in automatically detecting shot boundaries based on changes of visual and/or audio characteristics. There has also been considerable progress in indexing such video shots by automatically extracting keywords using techniques such as speech and text recognition. Shots detected by those techniques, however, are very fragmental. A single shot itself is rarely self-contained and therefore may not carry enough information to be a meaningful unit. A meaningful interval that interests common users generally spans several consecutive shots. There hardly exists any reliable technique for identifying all such meaningful intervals in advance so that any possible query can be answered.
In this paper, rather than identifying meaningful intervals beforehand, we shift our focus on how to compute them dynamically from fragmentarily indexed shots, when queries are issued. We achieve our goal by using two techniques — glues and filters. Glues are algebraic operations for composing all the longer intervals, which can be meaningful answers to a given query, from a set of shorter indexed shots. Glue operations do not count on any limit to the length of resulting intervals. Consequently, lengthy intervals containing several irrelevant shots are also expected to be composed as possible answers. Therefore, we provide filter functions so that such lengthy intervals are excluded from the answer set and only few relevant intervals are returned to the user. Both glues and filters possess certain algebraic properties that are useful for an efficient query processing.
This work is supported partly by the Japanese Ministry of Education under Grant-in-Aid for Scientific Research on Priority Area: “Advanced Databases”, No. 08244103 and partly by Research for the Future Program of JSPS under the Project “Researches on Advanced Multimedia Contents Processing”.
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Pradhan, S., Sogo, T., Tajima, K., Tanaka, K. (2000). A New Algebraic Approach to Retrieve Meaningful Video Intervals from Fragmentarily Indexed Video Shots. In: Arisawa, H., Catarci, T. (eds) Advances in Visual Information Management. VDB 2000. IFIP — The International Federation for Information Processing, vol 40. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35504-7_2
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DOI: https://doi.org/10.1007/978-0-387-35504-7_2
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