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A reduced order model for large numbers of head-related impulse responses (HRIRs) is proposed for real-time three-dimensional (3D) sound rendering. Independent spatial features are firstly extracted from measured HRIRs using independent component analysis (ICA). These spatial feature vectors are not only mutually statistical independent but independent from all the measured azimuths. Therefore filtering...
In particle collider experiments a huge amount of information is produced, but only a small part is relevant for physics characterization. An efficient filtering (trigger) system is required to guarantee that valuable signatures will be recorded and most of the background noise rejected. In previous works the standard linear independent component analysis (ICA) model was used for feature extraction...
Ear recognition is a new research area in the computer vision and pattern recognition field. This paper proposes a new ear biometrics system-compound structure classifier system for ear recognition (CSCSER), based on the research of ear recognition with algebraic feature. The system first makes rough classification to the human ears according to their geometric features. Then the algebra features...
In the paper, we propose a new method for ear recognition. Firstly, we extract global features using kernel principal component analysis (KPCA) technique and extract local features using independent component analysis (ICA) technique. Then we establish a correlation criterion function between two groups of feature vectors, extract their canonical correlation features according to this criterion, and...
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