Feature extraction and accurate classification of the emotion-related EEG-characteristics have a key role in success of emotion recognition systems. In this paper, an optimal EEG-based emotion recognition algorithm based on spectral features and neural network classifiers is proposed. In this algorithm, spectral, spatial and temporal features are selected from the emotion-related EEG signals by...

Previous work suggests that Gabor-wavelet-based methods can achieve high sensitivity and specificity for emotionspecified expressions (e.g., happy, sad) and single action units (AUs) of the Facial Action Coding System (FACS). This paper evaluates a Gabor-wavelet-based method to recognize AUs in image sequences of increasing complexity. A recognition rate of 83% is obtained for three single AUs ...

This paper describes a novel Gabor Feature Class$er (GFC) method for face recognition. The GFC method employs an enhanced Fisher discrimination model on an augmented Gabor feature vector; which is derived from the Gabor wavelet transformation o f f i c e images. The Gabor wavelets, whose kernels are similar to the 2 0 receptive field profiles of the nianinialian cortical simple cells, exhibit d...

We propose a multi-scale elastic graph matching (MS-EGM) algorithm for face detection, in which the conventional EGM is improved with two simple image processing techniques of the Gabor wavelet-based pyramid and the weak Gabor feature elimination. It is expected to solve difficulties of the real-time process in the conventional EGM. The Gabor wavelet-based pyramid effectively reduces not only t...

In this paper, we employ a new adaptive basis of functions — brushlets for extracting texture properties. Brushlets are functions which are well localized with only one peak in the frequency domain. Hence, a representation of texture in terms of spatial frequency distributions can be constructed. The Brushlet features are used in texture image retrieval experiments to assess its effectiveness b...

A new noncooperative iris recognition method is proposed. In this method, the iris features are extracted using a Gabor descriptor. The feature extraction and comparison are scale, deformation, rotation, and contrast-invariant. It works with off-angle and lowresolution iris images. The Gabor wavelet is incorporated with scale-invariant feature transformation (SIFT) for feature extraction to bet...

Let g be a continuous, compactly supported function on R such that the integer translates of g constitute a partition of unity. We show that the Gabor system (g, a, b), with window g and time-shift and frequency-shift parameters a, b > 0 has no lower frame bound larger than 0 if b = 2, 3, . . . and a > 0. In particular, (g, a, b) is not a Gabor frame if g is a continuous, compactly supported wa...

This paper proposed a new method of extracting texture features based on Gabor wavelet. In addition, the application of these features for bark classification applying radial basis probabilistic network (RBPNN) has been introduced. In this method, the bark texture feature is firstly extracted by filtering the image with different orientations and scales filters, then the mean and standard devia...

This paper describes a real-time technique for scale invariant object or face tracking with standard PC hardware. The tracking method is based on a low redundancy (compressed) object image representation. For image decomposition a fast non-iterative transform based on the odd-symmetric gabor functions is used, which guarantees on the one hand a low redundancy of the resulting representation and...