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This study suggests an application of human–robot interaction based on three-dimensional real-time monocular head pose tracker in which active appearance models (AAMs) are utilised to extract facial features. In order to improve texture model, two probabilistic approaches are proposed for principal component analysis in the presence of missing values. It is observed that using the suggested Bayesian...
A new iris recognition system based on complex wavelet Transforms is described. In this work iris recognition based on Gabor wavelet and Morlet wavelet are described. The most unique phenotypic feature visible in a person's face is the detailed texture of each eye's iris. The visible texture of a person's iris is encoded into a compact sequence of 2-D wavelet coefficients, which generate an ldquoiris...
Facial expression recognition can be divided into three steps: face detection, expression feature extraction and expression categorization. Facial expression feature extraction and categorization are the most key issue. To address this issue, we propose a method to combine local binary pattern (LBP) and embedded hidden markov model (EHMM), which is the key contribution of this paper. This paper first...
Building face models is an essential task in face recognition, tracking and etc. However, most of the current techniques require hand-labelling or special machinery such as cyber-scanner to extract the face model. In the paper, we propose an unsupervised algorithm to learn the face texture from video. The proposed approach models the video sequence as a mixture of dynamic face-layers and background...
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