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Several studies on micro-expression recognition have contributed mainly to accuracy improvement. However, the computational complexity receives lesser attention comparatively and therefore increases the cost of micro-expression recognition for real-time application. In addition, majority of the existing approaches required at least two frames (i.e., onset and apex frames) to compute features of every sample. This paper puts forward new facial graph features based on 68-point landmarks using Facial Action Coding System (FACS). The proposed feature extraction technique (FACS-based graph features) utilizes facial landmark points to compute graph for different Action Units (AUs), where the measured distance and gradient of every segment within an AU graph is presented as feature. Moreover, the proposed technique processes ME recognition based on single input frame sample. Results indicate that the proposed FACS-baed graph features achieve up to 87.33% of recognition accuracy with F1-score of 0.87 using leave one subject out cross-validation on SAMM datasets. Besides, the proposed technique computes features at the speed of 2 ms per sample on Xeon Processor E5-2650 machine.

We present in this paper a novel dataset (MMU VAAC) for violent actions against children recognition. This original dataset has been recorded using Microsoft Kinect with the usage of a child mannequin. MMU VAAC dataset contains skeleton joints, depth, and RGB modalities.

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Abstract:In this paper, a flexible, high computation speed and cost effective field programmable gate array (FPGA)-based speed controller for an induction motor with field-oriented control, (FOC) is presented. All the control functions including the space vector modulation based PWM waveform generation, field-oriented control algorithm and rotor flux position estimation have been realized using FPGA to reduce the total part count of the hardware prototype and hence provide a low cost solution. The constructed FOC IC consists of 6844 logic elements and is realized using Cyclone, EPIC12q240C8 from Altera Inc. The sampling rate can be programmed up to 100 MHz. Experimental result is included in this paper to illustrate the performance of the designed IC, FOCIC and the feasibility of integrating of SVM and FOC on single chip.