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Automatic face recognition across large pose changes is still a challenging problem. Previous solutions apply a transform in image space or feature space for normalizing the pose mismatch. For feature transform, the feature vector extracted on a probe facial image is transferred to match the gallery condition with regression models. Usually, the regression models are learned from paired gallery-probe...
Gabor features have been extensively used for facial image analysis due to their powerful representation capabilities. This paper focuses on selecting and combining multiple Gabor classifiers that are trained on, for example, different scales and local regions. The system exploits curvature Gabor features in addition to conventional Gabor features. Final classifier is obtained by combining selected...
This paper introduces a homogeneous Gabor feature based face recognition approach under uncontrolled conditions such as unexpected illumination changes, pose changes, blurring and facial expression changes. The system uses curvature Gabor features instead of conventional Gabor features, and the classifiers are obtained by applying PCLDA to the selected features. By combining some of the obtained classifiers...
In this paper, we present a multi-view facial expression classification system. The system utilizes local features extracted around automatically located facial landmarks using pose-dependent active appearance models. A pose-dependent ensemble of support vector machine classifiers assigns the given sample to one of the six basic expression classes. Extensive experiments have been conducted on the...
Facial analysis based on local regions/blocks usually outperforms holistic approaches because it is less sensitive to local deformations and occlusions. Moreover, modeling local features enables us to avoid the problem of high dimensionality of feature space. In this paper, we model the local face blocks with Gabor features and project them into a discriminant identity space. The similarity score...
Automatic recognition of facial expressions and head gestures plays an important role in a wide range of research area including sign language recognition and human-computer interaction. In this work, we adopt the well-performing self-similarity based action recognition method to classify facial expressions and head gestures. Additionally, we propose a novel approach for facial gesture recognition...
In this paper, face recognition systems that have been developed for smart interactions at the interACT Research Center is presented. The face recognition efforts at the interACT Research Center consist of development of a fast and robust face recognition algorithm and fully automatic face recognition systems that can be deployed for real-life smart interaction applications. The face recognition algorithm...
In this paper, we present a local appearance-based approach for 3-D face recognition. In the proposed algorithm, we first register the 3-D point clouds to provide a dense correspondence between faces. Afterwards, we analyze two mapping techniques-the closest-point mapping and the ray-casting mapping, to construct depth images from the corresponding well-registered point clouds. The depth images that...
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