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MMM
2008
Springer

Similarity Search in Multimedia Time Series Data Using Amplitude-Level Features

8 years 8 months ago
Similarity Search in Multimedia Time Series Data Using Amplitude-Level Features
Effective similarity search in multi-media time series such as video or audio sequences is important for content-based multi-media retrieval applications. We propose a framework that extracts a sequence of local features from large multi-media time series that reflect the characteristics of the complex structured time series more accurately than global features. In addition, we propose a set of suitable local features that can be derived by our framework. These features are scanned from a time series amplitude-levelwise and are called amplitude-level features. Our experimental evaluation shows that our method models the intuitive similarity of multi-media time series better than existing techniques.
Johannes Aßfalg, Hans-Peter Kriegel, Peer Kr
Added 31 May 2010
Updated 31 May 2010
Type Conference
Year 2008
Where MMM
Authors Johannes Aßfalg, Hans-Peter Kriegel, Peer Kröger, Peter Kunath, Alexey Pryakhin, Matthias Renz
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