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Unconstrained face recognition under varying views is one of the most challenging tasks, since the difference in appearances caused by poses may be even larger than that due to identity. In this paper, we exploit and analyze a novel pose normalization scheme for facial images under varying views via robust 3D shape reconstruction from single, unconstrained photos in the wild. Specifically, to address...
Trajectory-based features have become popular for action recognition and achieve the state-of-the-art results on a variety of datasets. In this paper, we propose a novel framework to improve the performance of action recognition. Specifically, we first apply the nonuniform sampling method to efficiently select features for given actions. The proposed hybrid super vector, namely fisher vector (FV)...
Facial motion tracking is a challenging task because of highly flexible head pose and facial expression. An extensible tracking framework is proposed in this paper. Within the framework, proper models are selected according to requirements and restrictions of the application, and different trackers can be constructed to handle different tasks. Experimental result shows that our tracker outperforms...
Facial expression tracking is a challenging task because the head pose may change in a large range and the expression is highly non-rigid. It can be formulized as an energy minimization problem. The two most important issues are the construction of the cost function and the selection of the initial value. In this paper, we present a fast and robust expression tracking algorithm called Composite Constraints...
In this paper, we present some extensions to Active Appearance Model and its extended view-based models are applied for tracking faces through wide angles. The extensions include:(1) a new multiband representation created by filtering the images with a set of orthogonal spatial filters and then applying a non-linear normalization to them, and (2)adding extra landmarks outside the facial region to...
This paper introduces a non-contact virtual mouse controlled by tracking the face movement. It is specially designed for the disabled with mobility impairments in the upper extremities. The whole work is based on the common Web camera. Improved optical flow algorithm is proposed through locating the facial features defined by active appearance model. Experiments show it is robust to the various background...
The Active Appearance Model (AAM) is a powerful generative method for modeling and registering deformable objects. However, model based on raw intensity tends to be sensitive to changes in conditions such as lighting. Thus model built on one data set may not perform well on another data set taken under different conditions. In this paper, a new low-cost preprocessing method for the local gradient...
Recently adaptive Gaussian mixture models have become increasingly popular on account of their strong ability to adapt to variations. In this paper, an algorithm based on adaptive mixture models is proposed to track facial actions in video. WSF Mixture Appearance Model is taken to depict image observation and an active learning scheme which combines fast convergence and temporal adaptability is presented...
Facial feature tracking is a crucial and challenging task in computer vision. Recently online-learning methods have become increasingly popular on account of their strong ability to adapt to variations and have achieved good results in tracking. However, all previous work used only raw intensity to build the model, which is very sensitive to condition changes. In this work, we present a real time,...
The active appearance model (AAM) is a powerful generative method for modeling and registering deformable objects. The project-out inverse compositional (POIC) method is one of the most common methods for AAM fitting and is also the fastest known method to date. However, it does not work well when the initialization is far from the optimum. In this paper, a two-stage fitting procedure based on POIC...
This paper presents a real time, fully automatic facial feature detection and tracking approach. The head pose and facial action is tracked by a modified Candide 3D wireframe model based on an improved image registration technique. An effective model shape and position initialization method is also proposed. Experimental results demonstrate that our system is accurate, robust and fast enough for common...
This paper proposes a framework of illumination normalization algorithm and two new image preprocessing methods according to the framework: piecewise gamma transformation (PGT) and piecewise histogram specification (PHS). They can be used to eliminate the effect of uneven lighting condition effectively and efficiently. The proposed methods have been evaluated based on the Yale face database B and...
Gabor feature has been widely viewed as a good representation method for face recognition. AdaBoost is an excellent machine learning technique. Learning Gabor feature based classifier using AdaBoost is one of the best face recognition algorithms. However, dimensionality of Gabor feature space usually is very high, which makes the training program need huge memory or else take a very long time to run...
Numerous studies in psychophysics and neurophysiological literatures have shown that both local and global features are important for representing and recognizing face. In this paper, a face recognition method, using local and global multi-resolution discriminative information, is proposed. First, face is represented by multi-scale and multi-orientation Gabor features. Then AdaBoost is employed to...
Gabor filters based features, with their good properties of space-frequency localization and orientation selectivity, seem to be the most effective features for face recognition currently. In this paper, we propose a kind of weighted Gabor complex features which combining Gabor magnitude and phase features in unitary space. Its weights are determined according to recognition rates of magnitude and...
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