In this paper we describe new methods to detect semantic concepts from digital video based on audible and visual content. Temporal Gradient Correlogram captures temporal correlations of gradient edge directions from sampled shot frames. Power-related physical features are extracted from short audio samples in video shots. Video shots containing people, cityscape, landscape, speech or instrumental sound are detected with trained self-organized maps and kNN classification results of audio samples. Test runs and evaluations in TREC 2002 Video Track show consistent performance for Temporal Gradient Correlogram and state-of-the-art precision in audio-based instrumental sound detection. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Rautiainen, M., Seppänen, T., Penttilä, J., & Peltola, J. (2003). Detecting semantic concepts from video using temporal gradients and audio classification. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. https://doi.org/10.1007/3-540-45113-7_26
Mendeley helps you to discover research relevant for your work.