A Modified Active Appearance Model Based on an Adaptive Artificial Bee Colony

Abstract

Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition.

Facial Expression Recognition Using Computer Vision: A Systematic Review

“…The shape information extracted with the AAM is used to compute a set of suitable parameters that highlights the appearance of the facial features. However, this method is highly sensitive to input images that have differences in pose, expression, and illumination, which were not included in the training set [83]. Figure 15 shows an example of this process.…”

Development of computer-aided model to differentiate COVID-19 from pulmonary edema in lung CT scan: EDECOVID-net

“…The coronavirus disease 2019 (COVID-19) originated in Wuhan in China and has spread rapidly worldwide since December 2019, causing a global panic. COVID-19 has been declared a Public Health Emergency of International Concern by the World Health Organization (WHO) [ 1 , 2 ]. According to the specifications published by the World Health Organization, as of May 16, 2021, more than 163 million laboratory-confirmed cases of COVID-19 had been documented globally [ 3 ], with patients often exhibiting pulmonary parenchymal opacity on chest radiography.…”

“…Early detection and treatment in severe cases is the key to reducing mortality, yielding favorable outcomes, and mitigating the potential spread and impact of infections [ 1 ].…”

Eye Localization Using Convolutional Neural Networks and Image Gradients

“…Eye gaze methods depend on identifying the precise location of the pupils [Kar and Corcoran 2017]. In order to ensure a good performance, many shape models need to position the initial shape very close to the correct location: a fast, low cost method for eye localization may provide a useful first guess [Abdulameer et al 2014]. Applications of an accurate algorithm for eye localization abound in the literature.…”