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Recognizing Frontal Face Images Using Hidden Markov Models ...
One-Sample Face Recognition Using HMM Model of Fiducial Areas. ... high dimensionality in one-sample face recognition is critical for its achievable recognition accuracy and feasibility in ...
John Adedapo OJO - Google Scholar Citations
One-sample face recognition using HMM model of fiducial areas. JA Ojo, SA Adeniran. International Journal of Image Processing (IJIP) 5 (1 ... Illumination invariant face detection using hybrid skin segmentation method. JA Ojo, SA Adeniran. Eur. J. Comput. ... Effective Smoke Detection Using Spatial-Temporal Energy and Weber Local Descriptors in ...
 LDA BASED FACE RECOGNITION BY USING HIDDEN MARKOV MODEL IN ...
Abstract: Hidden Markov model (HMM) is a promising method that works well for images with variations in lighting, facial expression, and orientation. Face recognition draws attention as a complex task due to noticeable changes produced on appearance by illumination, facial expression, size, orientation and other external factors....
Automatic local Gabor features extraction for face recognition
These fiducial points are ... Face recognition is a very challenging area in computer vision and pattern recognition due to variations in facial expressions, ... include hidden Markov model (HMM) [19], elastic bunch graph matching algorithm [3] and local feature analysis....
Face Recognition Using Hidden Markov Models - MAFIADOC.COM
P2D-HMM model size 64 5.5.2 P2D-HMM image size 64 5.6 6 6 ... To date, however, no work in face recognition using HMMs has been found and this dissertation investigates some of the aspects involved in classifying faces using this method. The work shows that, through the integration of a priori structural knowledge with statistical information ......
Dynamic face recognition: From human to machine vision ...
Much is known about the neural systems that subserve face recognition in adult humans and primates. Face-selective neurons have been found in the inferior temporal areas (TEa and TEm), the superior temporal sensory area, the amygdala, the ventral striatum (which receives input from the amygdala) and the inferior convexity .Using functional magnetic resonance imaging (fMRI), an area in the ......
Geometric Feature-Based Facial Expression Recognition in ...
These features are then used to train the GentleBoost classifiers, and build a Hidden Markov Model (HMM), in order to model the full temporal dynamic of the expressions. Rudovic and Pantic [ 27 ] introduce a method for head-pose invariant facial expression recognition that is based on a set of characteristic facial points, extracted using AAMs....
List of Open Access publications for International Journal ...
One-Sample Face Recognition Using HMM Model of Fiducial Areas : OJO, John Adedapo, Adeniran, Solomon A. Pages - 58 - 68 | Revised - 31-03-2011 | Published - 04-04-2011 : Full Text Available (246.9KB) MORE INFORMATION : Full Citation | Full Text PDF | Abstract | References | Related Articles
Human Recognition Using Face in Computed Tomography | DeepAI
Human Recognition Using Face in Computed Tomography. ... we focus on the face area in CT, which occupies the majority of CT images, especially in head and neck CT. ... Finally, we leverage transfer learning to adapt a pretrained face recognition model from face depth images in the RGB-D domain to the computed face depth images from CTs....
Face recognition from a single image per person: A survey ...
1. Introduction. As one of the few biometric methods that possess the merits of both high accuracy and low intrusiveness, face recognition technology (FRT) has a variety of potential applications in information security, law enforcement and surveillance, smart cards, access control, among others , , .For this reason, FRT has received significantly increased attention from both the academic and ...
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