A5006546933- Face recognition and analysis
- Facial Nerve Paralysis Treatment and Research
- Face and Expression Recognition
- Advanced Vision and Imaging
- Advanced Image Processing Techniques
- Generative Adversarial Networks and Image Synthesis
- Mathematical Analysis and Transform Methods
- AI in cancer detection
- Laser-induced spectroscopy and plasma
- Image Retrieval and Classification Techniques
- Image Enhancement Techniques
- Video Surveillance and Tracking Methods
- Atomic and Molecular Physics
- Laser-Plasma Interactions and Diagnostics
- Human Pose and Action Recognition
- Breast Lesions and Carcinomas
- Gaze Tracking and Assistive Technology
- Gene expression and cancer classification
Manchester Metropolitan University
2019-2023
Gwangju Institute of Science and Technology
2018
Institute for Basic Science
2018
University of Malaya
2016
With the growth of popularity facial micro-expressions in recent years, demand for long videos with micro- and macro-expressions remains high. Extended from SAMM, a dataset released 2016, this paper presents SAMM Long Videos spontaneous recognition spotting. consists 147 343 159 micro-expressions. The is FACS-coded detailed Action Units (AUs). We compare our Chinese Academy Sciences Macro-Expressions Micro-Expressions (CAS(ME) <sup xmlns:mml="http://www.w3.org/1998/Math/MathML"...
Facial expression spotting is the preliminary step for micro- and macro-expression analysis. The task of reliably such expressions in video sequences currently unsolved. Current best systems depend upon optical flow methods to extract regional motion features, before categorisation that into a specific class facial movement. Optical susceptible drift error, which introduces serious problem motions with long-term dependencies, as high frame-rate macro-expression. We propose purely deep...
Breast cancer is a threat to women worldwide. Manual delineation on breast ultrasound lesions time-consuming and operator dependent. Computer segmentation of can be challenging task due the ill-defined boundaries issues related speckle noise in images. The main contribution this paper compare performance computer classifier manual malignant benign classification. This we implement using multifractal approach database consists 120 images (50 70 lesions). result compared with Jaccard...
Long video datasets of facial macro- and micro-expressions remains in strong demand with the current dominance data-hungry deep learning methods. There are limited methods generating long videos which contain micro-expressions. Moreover, there is a lack performance metrics to quantify generated data. To address research gaps, we introduce new approach generate synthetic recommend assessment inspect dataset quality. For generation, use state-of-the-art generative adversarial network style...
Facial expression spotting is the preliminary step for micro- and macro-expression analysis. The task of reliably such expressions in video sequences currently unsolved. current best systems depend upon optical flow methods to extract regional motion features, before categorisation that into a specific class facial movement. Optical susceptible drift error, which introduces serious problem motions with long-term dependencies, as high frame-rate macro-expression. We propose purely deep...
In this article, we investigate the spontaneity issue in facial expression sequence generation. Current leading methods field are commonly reliant on manually adjusted conditional variables to direct model generate a specific class of expression. We propose neural network-based method which uses Gaussian noise generation process, removing need for manual control variables. Our takes two sequential images as input, with additive noise, and produces next image sequence. trained types models:...
With the growth of popularity facial micro-expressions in recent years, demand for long videos with micro- and macro-expressions remains high. Extended from SAMM, a dataset released 2016, this paper presents SAMM Long Videos spontaneous recognition spotting. consists 147 343 159 micro-expressions. The is FACS-coded detailed Action Units (AUs). We compare our Chinese Academy Sciences Macro-Expressions Micro-Expressions (CAS(ME)2) dataset, which only available fully annotated...