Jun Lee¹, Hanna Lee², Seong Chan Lee², Hyun Kwon^3,*

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 617-632, 2024, DOI:10.32604/cmc.2023.045768

Abstract Non-face-to-face psychological counseling systems rely on network technologies to anonymize information regarding client identity. However, these systems often face challenges concerning voice data leaks and the suboptimal communication of the client’s non-verbal expressions, such as facial cues, to the counselor. This study proposes a metaverse-based psychological counseling system designed to enhance client identity protection while ensuring efficient information delivery to counselors during non-face-to-face counseling. The proposed system incorporates a voice modulation function that instantly modifies/masks the client’s voice to safeguard their identity. Additionally, it employs real-time client facial expression recognition using an ensemble of decision trees to mirror the client’s… More >

Latifah Almuqren¹, Manar Ahmed Hamza^2,*, Abdullah Mohamed³, Amgad Atta Abdelmageed²

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4917-4933, 2023, DOI:10.32604/cmc.2023.037738

Abstract Face recognition technology automatically identifies an individual from image or video sources. The detection process can be done by attaining facial characteristics from the image of a subject face. Recent developments in deep learning (DL) and computer vision (CV) techniques enable the design of automated face recognition and tracking methods. This study presents a novel Harris Hawks Optimization with deep learning-empowered automated face detection and tracking (HHODL-AFDT) method. The proposed HHODL-AFDT model involves a Faster region based convolution neural network (RCNN)-based face detection model and HHO-based hyperparameter optimization process. The presented optimal Faster RCNN model precisely recognizes the face and… More >

Boxia Hu^1,2,*, Huihuang Zhao¹, Yufei Yang^1,3, Bo Zhou⁴, Alex Noel Joseph Raj⁵

Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1549-1560, 2020, DOI:10.32604/iasc.2020.011721

Abstract Face tracking is one of the most challenging research topics in computer vision. This paper proposes a framework to track multiple faces in video sequences automatically and presents an improved method based on feature fusion and neural network for multiple faces tracking in a video. The proposed method mainly includes three steps. At first, it is face detection, where an existing method is used to detect the faces in the first frame. Second, faces tracking with feature fusion. Given a video that has multiple faces, at first, all faces in the first frame are detected correctly by using an existing… More >

Cheng Wang¹, Jianguo Ning¹, Tianbao Ma¹

CMC-Computers, Materials & Continua, Vol.22, No.1, pp. 73-96, 2011, DOI:10.3970/cmc.2011.022.073

Abstract In this paper, we report high resolution simulations using a fifth-order weighted essentially non-oscillatory (WENO) scheme with a third-order TVD Runge-Kutta time stepping method to examine the features of the detonation for gas and condensed explosives. A two-stage chemical reaction model and an ignition and growth model are employed to describe the chemical reaction process for gas and condensed explosives. Based on the Steger-Warming vector flux splitting method, a splitting method is employed when the vector flux does not satisfy the homogeneity property for simulating detonation wave propagation for condensed explosives. The sensibility of flame propagation process and explosion overpressure… More >