Guest Editors
Dr. Khalil Khan, Pak-Austria Institute of Applied Sciences and Technology, Pakistan.
Dr. Rehan Ullah Khan, Qassim University, KSA.
Dr. Kashif Ahmad, Hamad Bin Khalifa University, Qatar.
Summary
Human face image analysis describes several face perceptions tasks, including face detection, race and age classification, face recognition, gender recognition, etc. These attributes have been given attention in recent days in Computer Vision (CV) research community due to large scale applications. Face image analysis plays an important role in real world applications, including augmentation, biometrics, animations, surveillance, human computer interaction and several other applications. Despite these research developments, human face analysis is still difficult and challenging task due to reasons such as poor imagery conditions, complicated facial expressions, complex background etc. Human face image analysis has more complication in the un-constrained and real-world conditions.
With the emergence of deep learning methods face image analysis is excellently addressed by computer vision researchers. This special issue looks forward to novel techniques using deep learning and machine learning, covering some new exiting research findings. We welcome high quality research and review articles to our special issue.
Keywords
Machine learning and Artificial Intelligence for Preserving and completion of facial identity.
Deep learning for Face image de-blurring.
Facial landmark extraction through deep learning.
Face swapping and Face beautification using deep learning.
Head pose estimation, facial expression, age, race, and gender recognition.
Portrait segmentation and making using deep learning.
Advances in face recognition and face detection with emergence of deep learning.
Published Papers
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Open Access
ARTICLE
A Template Matching Based Feature Extraction for Activity Recognition
Muhammad Hameed Siddiqi, Helal Alshammari, Amjad Ali, Madallah Alruwaili, Yousef Alhwaiti, Saad Alanazi, M. M. Kamruzzaman
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 611-634, 2022, DOI:10.32604/cmc.2022.024760
（This article belongs to this Special Issue:
Face Image Analysis Using Deep Learning)
Abstract Human activity recognition (HAR) can play a vital role in the monitoring of human activities, particularly for healthcare conscious individuals. The accuracy of HAR systems is completely reliant on the extraction of prominent features. Existing methods find it very challenging to extract optimal features due to the dynamic nature of activities, thereby reducing recognition performance. In this paper, we propose a robust feature extraction method for HAR systems based on template matching. Essentially, in this method, we want to associate a template of an activity frame or sub-frame comprising the corresponding silhouette. In this regard, the template is placed on…
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