Emotion plays an important role in communication. For human–computer interaction, facial expression recognition has become an indispensable part. Recently, deep neural networks (DNNs) are widely used in this field and they overcome the limitations of conventional approaches. However, application of DNNs is very limited due to excessive hardware specifications requirement. Considering low hardware specifications used in real-life conditions, to gain better results without DNNs, in this paper, we propose an algorithm with the combination of the oriented FAST and rotated BRIEF (ORB) features and Local Binary Patterns (LBP) features extracted from facial expression. First of all, every image is passed through face detection algorithm to extract more effective features. Second, in order to increase computational speed, the ORB and LBP features are extracted from the face region; specifically, region division is innovatively employed in the traditional ORB to avoid the concentration of the features. The features are invariant to scale and grayscale as well as rotation changes. Finally, the combined features are classified by Support Vector Machine (SVM). The proposed method is evaluated on several challenging databases such as Cohn-Kanade database (CK+), Japanese Female Facial Expressions database (JAFFE), and MMI database; experimental results of seven emotion state (neutral, joy, sadness, surprise, anger, fear, and disgust) show that the proposed framework is effective and accurate.
Based on both adaptive and fuzzy control techniques, this paper proposes a faulttolerant control (FTC) approach for near space vehicle (NSV) re-entry attitude dynamics with a stuck actuator fault. A Takagi-Sugeno fuzzy model is used to describe complex NSV attitude dynamics. The principle of this FTC approach is to design an iterative learning observer, which is used to estimate the system state and produce control input adjustment and then to reconfigure the control law to compensate for the effect of the stuck actuator. The FTC scheme ensures that the NSV output dynamics asymptotically track that of a reference model under both fault-free conditions and with a stuck actuator. The boundedness of the error dynamics is analysed using the Lyapunov stability theory. Finally, simulation results are given to illustrate the effectiveness and potential of the proposed FTC technique.
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