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In this paper, we address the 3D eye gaze estimation problem using a low-cost, simple-setup, and non-intrusive consumer depth sensor (Kinect sensor). We present an effective and accurate method based on 3D eye model to estimate the point of gaze of a subject with the tolerance of free head movement. To determine the parameters involved in the proposed eye model, we propose i) an improved convolution-based...
This paper investigates gaze estimation solutions for interacting children with Autism Spectrum Disorders (ASD). Previous research shows that satisfactory accuracy of gaze estimation can be achieved in constrained settings. However, most of the existing methods can not deal with large head movement (LHM) that frequently happens when interacting with children with ASD scenarios. We propose a gaze estimation...
Human face analysis is the basis for many other computer vision tasks, such as camera surveillance, entrance authorization and age estimation. With 3D face models, the vision task based on facial analysis can usually achieve a higher accuracy than the 2D cases since it provides more information with the additional dimension. However, most existing 3D face reconstruction methods suffer from complicated...
Local binary pattern on three orthogonal planes (LBP-TOP) is one of the most popular method for dynamic texture analysis and has been successfully applied to facial expression analysis. Yet an effective LBP-TOP operator highly relies on preprocessing. And, like many appearance-based approaches, this approach reserves more identity-related cues rather than expression. In this work, we propose a fully...
Facial pose estimation is an important part for facial analysis such as face and facial expression recognition. In most existing methods, facial features are essential for facial pose estimation. However, occluded key features and uncontrolled illumination of face images make the facial feature detection vulnerable. In this paper, we propose methods for facial pose estimation via dense reconstruction...
We propose a novel platform to flexibly synthesize any arbitrary meaningful facial expression in the absence of actor performance data for that expression. With techniques from computer graphics, we synthesized random arbitrary dynamic facial expression animations. The synthesis was controlled by parametrically modulating Action Units (AUs) taken from the Facial Action Coding System (FACS). We presented...
This paper proposed how to recognize face image using learning classifier. The main idea of SVM is to give an optimal hyper-plane for two categories classification issues. The max value of k decision functions is used to decide sample data x belong to which class. Experimental result shows that the proposed face recognition algorithm is effective.
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