High-Level Feature Extraction Using SIFT GMMs and Audio Models

Abstract

We propose a statistical framework for high-level feature extraction that uses SIFT Gaussian mixture models (GMMs) and audio models. SIFT features were extracted from all the image frames and modeled by a GMM. In addition, we used mel-frequency cepstral coefficients and ergodic hidden Markov models to detect high-level features in audio streams. The best… (More)
DOI: 10.1109/ICPR.2010.787

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