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- W3194928485 abstract "Video delivery over the Internet has been becoming a commodity in recent years, owing to the widespread use of Dynamic Adaptive Streaming over HTTP (DASH). The DASH specification defines a hierarchical data model for Media Presentation Descriptions (MPDs) in terms of segments. This paper focuses on segmenting video into multiple shots for encoding in Video on Demand (VoD) HTTP Adaptive Streaming (HAS) applications. Therefore, we propose a novel Discrete Cosine Transform (DCT) feature-based shot detection and successive elimination algorithm for shot detection and compare it against the default shot detection algorithm of the x265 implementation of the High Efficiency Video Coding (HEVC) standard. Our experimental results demonstrate that our proposed feature-based pre-processor has a recall rate of 25% and an F-measure of 20% greater than the benchmark algorithm for shot detection." @default.
- W3194928485 created "2021-08-30" @default.
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- W3194928485 date "2021-09-19" @default.
- W3194928485 modified "2023-10-16" @default.
- W3194928485 title "Efficient Content-Adaptive Feature-Based Shot Detection for HTTP Adaptive Streaming" @default.
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- W3194928485 doi "https://doi.org/10.1109/icip42928.2021.9506092" @default.
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