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Robust facial feature tracking

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Cognitive Informatics CI is the transdisciplinary study into the internal information processing mechanisms and processes of the Natural Intelligence NI — human brains and minds — and their engineering applications in computing, ICT, and healthcare industries. It is a cutting-edge and multidisciplinary research area that tackles the fundamental problems shared by modern informatics, computation, software engineering, AI, cybernetics, cognitive science, neuropsychology, medical science, systems science, philosophy, linguistics, economics, management science, and life sciences. As an aspect of the major cognitive processes, emotion has been studied by many researchers Wang, b; Picard, In the research works of AC, emotion recognition is one of the most basic and important modules in affective computing.
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Robust facial feature tracking under varying face pose and facial expression

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Robust face and facial feature tracking for gaze estimation

Facial features, such as eyes, eyebrows, nose and mouth, and their spatial arrangement, are important for the facial interpretation tasks based on face images, such as face recognition, facial expression analysis and face animation. Therefore, locating these facial features in a face image accurately is a crucial step for these tasks to perform well. However, in reality, the appearance of the facial features in the images varies significantly among different individuals. Even, for a specific person, the appearance of the facial features is easily affected by the lighting conditions, face orientations and facial expressions, etc. Therefore, accurate facial feature detection and tracking still remains a very challenging task, especially under different illuminations, face orientations and facial expressions, etc. In our research, we proposed an effective approach to detect and track twenty-eight facial features from the face images with different facial expressions under various face orientations in real time.
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A Robust Shape Reconstruction Method for Facial Feature Point Detection

Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: This paper presents a hierarchical multi-state pose-dependent approach for facial feature detection and tracking under varying facial expression and face pose.
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Facial feature point detection has been receiving great research advances in recent years. Numerous methods have been developed and applied in practical face analysis systems. However, it is still a quite challenging task because of the large variability in expression and gestures and the existence of occlusions in real-world photo shoot. In this paper, we present a robust sparse reconstruction method for the face alignment problems.
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