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This article outlines issues related to automated film analysis for archived documentaries and explores examples of the applicability of existing content-based retrieval methods.
The contribution of this paper consists of a framework for video comparison that allows for the analysis of different movie versions. Furthermore, a second contribution is an evaluation of state-of-the-art, local feature-based approaches for content-based video retrieval in a real world scenario. Eventually, the experimental results show the outstanding performance of a simple, edge-based descriptor...
Given a broad set of content-based audio features, we employ principal component analysis for the composition of an optimal feature set for environmental sounds. We select features based on quantitative data analysis (factor analysis) and conduct retrieval experiments to evaluate the quality of the feature combinations. Retrieval results show that statistical data analysis gives useful hints for feature...
The paper introduces a novel interdisciplinary project addressing the analysis of historical artistic films. The type of employed material has not been subject to automatic analyses, so far. It poses challenges in all areas of content-based analysis and retrieval due to its complex temporal structure and due to substantial degradations. We propose robust features and a method for shot cut detection...
Until recently few research has been performed in the area of animal sound retrieval. The authors identify state-of-the-art techniques in general purpose sound recognition by a broad survey of literature. Based on the findings, this paper gives a thorough investigation of audio features and classifiers and their applicability in the domain of animal sounds. We introduce a set of novel audio descriptors...
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