A New Fast and Accurate Heuristic for the Automatic Scene Detection Problem

Daniele Catanzaro, Raffaele Pesenti and Roberto Ronco
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Daniele Catanzaro: Université catholique de Louvain, LIDAM/CORE, Belgium

No 2021022, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: The Automatic Scene Detection Problem (ASDP) is a combinatorial optimization problem that arises in the context of video processing and that has a central role in the management, storing and content retrieval of videos. The problem consists of partitioning the shots of a given video into scenes by optimizing a measure related to the similarity between the given shots. In this article, we build up upon the results from the literature on the ASDP in order to design a new approximate solution algorithm able to outperform the current state-of-the-art both in terms of speed and quality of the solution.

Keywords: Combinatorial Optimization; Video Processing; Segmentation; Scene Detection; Heuristics; Dynamic Programming (search for similar items in EconPapers)
Pages: 18
Date: 2021-01-01
New Economics Papers: this item is included in nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:cor:louvco:2021022

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