Dense feature extraction is becoming increasingly popular in face recognition. Face recognition is a vital component for authorization and security. In earlier days, CCA (Canonical Correlation Analysis) and SIFT (Scale Invariant Feature Transforms) was used for face recognition. Since multi scale extraction is not possible with these existing methods, a new approach to dense feature extraction ...

The enrollment of face templates and eye windows in a detection system of eye blinking or an estimation system of face orientation requires the extraction of face region and eye region in a face image. In order to automatically enroll face templates and eye windows with various face orientations, we present a novel method of extracting face region and eye window by using a set of gray-scale ima...

The problem of face detection remains challenging because faces are non-rigid objects that have a high degree of variability with respect to head rotation, illumination, facial expression, occlusion, and aging. This paper employs a novel technique, known as Locally Linear Embedding (LLE), for solving the face detection problem. The LLE method performs dimensionality reduction on data for learni...

Human face detection has always been an important problem for face, expression and gesture recognition. Though numerous attempts have been made to detect and localize faces, these approaches have made assumptions that restrict their extension to more general cases. In this research, we propose a feature-based face detection algorithm that can be easily extended to detect faces under diierent sc...

In this paper, a robust real-world video based open-set face recognition system is presented. This system is designed for general small-scale convenience applications, which can be used for providing customized services. In the developed prototype, the system identifies a person in question and conveys customized information according to the identity. Since it does not require any cooperation o...

Multi-scale local phase quantization (MLPQ) is an effective face descriptor for face recognition. In previous work, MLPQ is computed by using Short-term Fourier Transformation (SFT) in local regions and the high-dimension histogram based features are extracted for face representation. This paper tries to improve MLPQ based face recognition in terms of accuracy and efficiency. It has two main co...