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This paper describes a world first versatile recognition algorithm suitable for processing images, sound and acceleration signals simultaneously with extremely low calculation cost while maintaining high recognition rates. There are three main contributions. The first is the introduction of a versatile recognition using Haar-like feature for images, sound and acceleration signals. The novel 1-D Haar-like...
In this paper, novel 2 one-dimensional (1D) Haar-like filtering techniques are proposed as a new and low calculation cost feature extraction method suitable for 3D acceleration signals based human activity recognition. Proposed filtering method is a simple difference filter with variable filter parameters. Our method holds a strong adaptability to various classification problems which no previously...
Sound feature extraction Mel frequency cepstral coefficients (MFCC) and classification dynamic time warping (DTW) algorithms are applied to recognizing the background sounds in the human daily activities. Applying these algorithms to fourteen typical daily activity sounds, average recognition accuracy of 92.5% can be achieved. In these algorithms, how two parameters (i.e., Mel filters number and frame-to-frame...
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