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.

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.

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

Raffaele Pesenti;
2021-01-01

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3741666
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