A novel Monogenic Directional Pattern (MDP) and pseudo-Voigt kernel for facilitating the identification of facial emotions

Alphonse, A. Sherly; Dejey,

doi:10.1016/j.jvcir.2017.10.008

Cited by 14 publications

(6 citation statements)

References 39 publications

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“…A novel image pre-processing technique that combines optimised preprocessing filters with a CNN-SVM classifier was implemented [44]. A unique Monogenic Directional Pattern (MDP) was proposed to speed up the selection of the optimum kernel [45]. The commonly used kernel for dimension reduction is a Generalised Discriminant Analysis (GDA) based on a unique pseudo-Voigt kernel (PVK) [45].…”

Section: Face-basedmentioning

confidence: 99%

“…A unique Monogenic Directional Pattern (MDP) was proposed to speed up the selection of the optimum kernel [45]. The commonly used kernel for dimension reduction is a Generalised Discriminant Analysis (GDA) based on a unique pseudo-Voigt kernel (PVK) [45]. A new spatiotemporal restricted boltzmann machines (RBM)-based model was developed to learn the correlations (or transformations) quickly between image pairings associated with distinct facial emotions [46].…”

Section: Face-basedmentioning

confidence: 99%

“…[82] Custom colour ball dataset Primary Colour ball datasets are composed of approximately 500 photos that have been gathered and labelled. [27], [94], [75], [9], [84], [31], [45], [46], [33], [41], [42], [43], [50], [38], [39], [53] Extended Cohn-Kanade (CK+) Secondary It is a database of facial expressions that contains 327 annotated video sequences from 123 participants in eight different expression states. The dataset"s subjects are diverse in age, gender and ethnic origin, making it one of the most preferred datasets for FER research.…”

Section: Name Of Dataset Type Descriptionmentioning

confidence: 99%

“…[21] Unknown Primary The data were acquired from 16 study participants using the microphones of the Pepper robot for audio recording, and the robot captured the images of the user drawings for the visuospatial and executive skills, which were then analysed. [48], [45], [33], [24], [50], [38], [53], [54] The Japanese Female Facial Expression (JAFFE) Dataset Secondary It features 213 facial photos of 10 Japanese women, each with seven different facial expressions: anger, disgust, fear, happiness, neutral, sadness and surprise. The image has a resolution of 256 × 256 pixels.…”

Section: Primarymentioning

confidence: 99%

“…The recognition accuracies of most traditional approaches, such as Haar cascade, HOG descriptor, neural networks and deep learning, largely depend on feature extraction [50] [35]. An issue in a feature-extracted process is reducing the time spent on selecting the best kernel [45] [43]. The majority of current automated FER models are based on manually engineered features and pooled information from selected video frames.…”

Section: Challenges Related To Classification Accuracymentioning

confidence: 99%

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Robotics Utilization in Automatic Vision-Based Assessment Systems From Artificial Intelligence Perspective: A Systematic Review

et al. 2022

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This study presents a systematic review of the automatic vision-based assessment systems and models from related fields over the last 6 years. Many studies focus on automatic vision-based assessment in the area of robotics, artificial intelligence and virtual reality or augmented reality (AR) to enhance the communication between humans and machines for general purposes. Three reliable databases, IEEEXplore, Science Direct and Web of Science, were used to obtain relevant studies on the given topic. Several stages of filtering and scanning were applied according to the inclusion/exclusion criteria to filter the obtained 3505 papers from 2015 to 2020. Finally, 97 papers met the criteria. They were classified into four main categories based on their field by following the scientific taxonomy: computer-vision-based, robotics-based, AR-based and hybrid-based categories, accounting for 42.26% (n = 41/97 papers), 48.45% (n = 47/97 papers), 6.18% (n = 6/97 papers) and 4.12% (n = 4/97 papers), respectively. Subsequently, a deep and critical analysis of this multifield systematic review highlighted new research opportunities, motivations, challenges and recommendations that need attention to integrate interdisciplinary studies. Thus, automatic vision-based assessment, which is a field requiring automated solutions, tools and methods, enhances the ability of the assistive technology and facilitates the interaction of individuals with machines. Many studies have been conducted on the automatic vision-based assessment systems and their subtypes to promote accurate communication and performance evaluation in human-machine interaction. This study can provide researchers with useful guides and valuable information for future research. This study also addresses the ambiguity of automatic vison-based assessment models in interdisciplinary fields.

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Section: Face-basedmentioning

confidence: 99%