scholarly journals An Adaptive Face Tracker with Application in Yawning Detection

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1494
Author(s):  
Aasim Khurshid ◽  
Jacob Scharcanski
Keyword(s):  
State Of The Art ◽  
Tracking Error ◽  
Face Tracking ◽  
Facial Features ◽  
Local Models ◽  
Tracking Errors ◽  
Detection Scheme ◽  
Search Mechanism ◽  
The Face ◽  
Divergence Estimate

In this work, we propose an adaptive face tracking scheme that compensates for possible face tracking errors during its operation. The proposed scheme is equipped with a tracking divergence estimate, which allows to detect early and minimize the face tracking errors, so the tracked face is not missed indefinitely. When the estimated face tracking error increases, a resyncing mechanism based on Constrained Local Models (CLM) is activated to reduce the tracking errors by re-estimating the tracked facial features’ locations (e.g., facial landmarks). To improve the Constrained Local Model (CLM) feature search mechanism, a Weighted-CLM (W-CLM) is proposed and used in resyncing. The performance of the proposed face tracking method is evaluated in the challenging context of driver monitoring using yawning detection and talking video datasets. Furthermore, an improvement in a yawning detection scheme is proposed. Experiments suggest that our proposed face tracking scheme can obtain a better performance than comparable state-of-the-art face tracking methods and can be successfully applied in yawning detection.

scholarly journals Effect of the Orientation Schemes of the Energy Collection Element on the Optical Performance of a Parabolic Trough Concentrating Collector

Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 128 ◽  
Author(s):  
Majedul Islam ◽  
Prasad Yarlagadda ◽  
Azharul Karim
Keyword(s):  
Monte Carlo ◽  
State Of The Art ◽  
Tracking Error ◽  
Surface Group ◽  
Energy Performance ◽  
Optical Performance ◽  
Extended Version ◽  
Parabolic Trough ◽  
Tracking Errors ◽  
Optical Efficiency

While the circular shape is currently the proven optimum design of the energy collection element (ECE) of a parabolic trough collector, that is yet to be confirmed for parabolic trough concentrating collectors (PTCCs) like trough concentrating photovoltaic collectors and hybrid photovoltaic/thermal collectors. Orientation scheme of the ECE is expected to have significant effect on the optical performance including the irradiance distribution around the ECE and the optical efficiency, and therefore, on the overall energy performance of the PTCC. However, little progress addressing this issue has been reported in the literature. In this study, a thorough investigation has been conducted to determine the effect of the orientation schemes of ECE on the optical performance of a PTCC applying a state-of-the-art Monte Carlo ray tracing (MCRT) technique. The orientation schemes considered are a flat rectangular target and a hollow circular, semi-circular, triangular, inverted triangular, rectangular and rectangle on semi-circle (RSc). The effect of ECE defocus, Sun tracking error and trough rim angle on the optical performance is also investigated. The MCRT study reveals that the ECE orientation schemes with a curved surface at the trough end showed much higher optical efficiency than those with a linear surface under ideal conditions. ECEs among the linear surface group, the inverted triangular orientation exhibited the highest optical efficiency, whereas the flat and triangular ones exhibited the lowest optical efficiency, and the rectangular one was in between them. In the event of defocus and tracking errors, a significant portion of the concentrated light was observed to be intercepted by the surfaces of the rectangular and RSc ECEs that are perpendicular to the trough aperture. This is an extended version of a published work by the current authors, which will help to design an optically efficient ECE for a parabolic trough concentrating collector.

scholarly journals Multimodal verge for scale and pose variant real time face tracking and recognition

2019 ◽  
Vol 13 (2) ◽  
pp. 665
Author(s):  
Ramkumar Govindaraj ◽  
E. Logashanmugam
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Real Time ◽  
Research Field ◽  
Face Tracking ◽  
Low Rank ◽  
Facial Features ◽  
The Face ◽  
Low Rank Representation ◽  
Tracking And Recognition

In recent times face tracking and face recognition have turned out to be increasingly dynamic research field in image processing. This work proposed the framework DEtecting Contiguous Outliers in the LOw-rank Representation for face tracking, in this algorithm the background is assessed by a low-rank network and foreground articles can be distinguished as anomalies. This is suitable for non-rigid foreground motion and moving camera. The face of a foreground person is caught from the frame and then it is contrasted and the speculated pictures stored in the dataset. Here we used Viola-Jones algorithm for face recognition. This approach outperforms the traditional algorithms on multimodal video methodologies and it works adequately on extensive variety of security and surveillance purposes. Results on the continuous demonstrate that the proposed calculation can correctly obtain facial features points. The algorithm is relegate on the continuous camera input and under ongoing ecological conditions.

Age-Invariant Face Recognition Using Triangle Geometric Features

2015 ◽  
Vol 29 (05) ◽  
pp. 1556006 ◽  
Author(s):  
Amal Seralkhatem Osman Ali ◽  
Vijanth Sagayan Asirvadam ◽  
Aamir Saeed Malik ◽  
Mohamed Meselhy Eltoukhy ◽  
Azrina Aziz
Keyword(s):  
Face Recognition ◽  
State Of The Art ◽  
Facial Recognition ◽  
Research Network ◽  
Facial Features ◽  
Age Difference ◽  
Facial Aging ◽  
The Face ◽  
Recognition Systems ◽  
Mathematical Relationships

Whilst facial recognition systems are vulnerable to different acquisition conditions, most notably lighting effects and pose variations, their particular level of sensitivity to facial aging effects is yet to be researched. The face recognition vendor test (FRVT) 2012's annual statement estimated deterioration in the performance of face recognition systems due to facial aging. There was about 5% degradation in the accuracies of the face recognition systems for each single year age difference between a test image and a probe image. Consequently, developing an age-invariant platform continues to be a significant requirement for building an effective facial recognition system. The main objective of this work is to address the challenge of facial aging which affects the performance of facial recognition systems. Accordingly, this work presents a geometrical model that is based on extracting a number of triangular facial features. The proposed model comprises a total of six triangular areas connecting and surrounding the main facial features (i.e. eyes, nose and mouth). Furthermore, a set of thirty mathematical relationships are developed and used for building a feature vector for each sample image. The areas and perimeters of the extracted triangular areas are calculated and used as inputs for the developed mathematical relationships. The performance of the system is evaluated over the publicly available face and gesture recognition research network (FG-NET) face aging database. The performance of the system is compared with that of some of the state-of-the-art face recognition methods and state-of-the-art age-invariant face recognition systems. Our proposed system yielded a good performance in term of classification accuracy of more than 94%.

Face Alignment for Robust to Background and Occlusion Using Variation of 3D Reference Shape

2013 ◽  
Vol 717 ◽  
pp. 511-516
Author(s):  
Seok Hoon Kang
Keyword(s):  
Face Tracking ◽  
Face Alignment ◽  
Alignment Error ◽  
Local Models ◽  
Tracking Method ◽  
Complex Background ◽  
Reference Shape ◽  
The Face

A Constrained Local Models is face tracking method based on variation of shape in the Allowable Shape Domain. The CLMs perform optimize strategy in patch. It has problem because occlusion and background. In this paper, variation of shape is constrained for solving this problem.The generating of shape allows only shape adjusted translation, rotation, scale. The proposed method prevent that the shape generate to abnormal forms. As a result, the alignment error is about 4.2 pixels in environment has complex background. Also, when part of the face occluded, the alignment error is about 18.1pixels.

scholarly journals Kernelized Heterogeneity-Aware Cross-View Face Recognition

2021 ◽  
Vol 4 ◽  
Author(s):  
Tejas I. Dhamecha ◽  
Soumyadeep Ghosh ◽  
Mayank Vatsa ◽  
Richa Singh
Keyword(s):  
Face Recognition ◽  
Case Studies ◽  
Near Infrared ◽  
State Of The Art ◽  
Facial Features ◽  
Digital Photo ◽  
Face Matching ◽  
The Face ◽  
Improved Performance ◽  
Heterogeneity Variance

Cross-view or heterogeneous face matching involves comparing two different views of the face modality such as two different spectrums or resolutions. In this research, we present two heterogeneity-aware subspace techniques, heterogeneous discriminant analysis (HDA) and its kernel version (KHDA) that encode heterogeneity in the objective function and yield a suitable projection space for improved performance. They can be applied on any feature to make it heterogeneity invariant. We next propose a face recognition framework that uses existing facial features along with HDA/KHDA for matching. The effectiveness of HDA and KHDA is demonstrated using both handcrafted and learned representations on three challenging heterogeneous cross-view face recognition scenarios: (i) visible to near-infrared matching, (ii) cross-resolution matching, and (iii) digital photo to composite sketch matching. It is observed that, consistently in all the case studies, HDA and KHDA help to reduce the heterogeneity variance, clearly evidenced in the improved results. Comparison with recent heterogeneous matching algorithms shows that HDA- and KHDA-based matching yields state-of-the-art or comparable results on all three case studies. The proposed algorithms yield the best rank-1 accuracy of 99.4% on the CASIA NIR-VIS 2.0 database, up to 100% on the CMU Multi-PIE for different resolutions, and 95.2% rank-10 accuracies on the e-PRIP database for digital to composite sketch matching.

The face of a killer: How facial features influence the negation of guilt

2011 ◽  
Author(s):  
Lieke Curfs ◽  
Rob Holland ◽  
Jose Kerstholt ◽  
Daniel Wigboldus
Keyword(s):  
Facial Features ◽  
The Face

FACE RECOGNITION USING FUZZY INFERENCE SYSTEM

2009 ◽  
Vol 8 (3) ◽  
pp. 887-897
Author(s):  
Vishal Paika ◽  
Er. Pankaj Bhambri
Keyword(s):  
Neural Networks ◽  
Fuzzy Inference ◽  
Facial Features ◽  
Facial Appearance ◽  
Feature Points ◽  
Inference System ◽  
Detection Techniques ◽  
The Face ◽  
Hair Style ◽  
Facial Images

The face is the feature which distinguishes a person. Facial appearance is vital for human recognition. It has certain features like forehead, skin, eyes, ears, nose, cheeks, mouth, lip, teeth etc which helps us, humans, to recognize a particular face from millions of faces even after a large span of time and despite large changes in their appearance due to ageing, expression, viewing conditions and distractions such as disfigurement of face, scars, beard or hair style. A face is not merely a set of facial features but is rather but is rather something meaningful in its form.In this paper, depending on the various facial features, a system is designed to recognize them. To reveal the outline of the face, eyes, ears, nose, teeth etc different edge detection techniques have been used. These features are extracted in the term of distance between important feature points. The feature set obtained is then normalized and are feed to artificial neural networks so as to train them for reorganization of facial images.

Facial Surface Anthropometric Features and Measurements With an Emphasis on Rhinoplasty

2021 ◽  
Author(s):  
M Mazhar Celikoyar ◽  
Michael F Perez ◽  
M Ilhan Akbas ◽  
Oguzhan Topsakal
Keyword(s):  
Surgical Planning ◽  
Medical Literature ◽  
Facial Features ◽  
Post Surgery ◽  
Anthropometric Features ◽  
The Face ◽  
Narrative Literature ◽  
Narrative Literature Review ◽  
Objective Outcomes ◽  
A Current

Abstract Background Facial features and measurements are utilized to analyze patients’ faces for various reasons, including surgical planning, scientific communications, patient-surgeon communications, and post-surgery evaluations. Objectives There are numerous descriptions regarding these features and measurements scattered throughout the literature and we did not encounter a current compilation of these parameters in the medical literature. Methods A narrative literature review of the published medical literature for facial measurements used for facial analysis in rhinoplasty was done through the electronic databases MEDLINE/PubMed and Google Scholar, along with a citation search. Results A total of 61 facial features were identified. 45 points (25 bilateral, 20 unilateral), five lines (three bilateral, two unilateral), eight planes, and three areas. A total of 122 measurements were identified: 48 distances (6 bilateral, 42 unilateral), 57 angles (13 bilateral, 44 unilateral), and 17 ratios. Supplemental Figures were created to depict all features and measurements using either a frontal, lateral or basal view of the face. Conclusions This paper provides the most comprehensive and current compilation of facial measurements to date. We believe this compilation will guide further developments (methodologies and software tools) for analyzing nasal structures and assessing the objective outcomes of facial surgeries, in particular rhinoplasty. Moreover, it will improve the communication as a reference for facial measurements of facial surface anthropometry, in particular rhinoplasty.

scholarly journals Window dressing in the Active Share scores in publicly reported portfolios

2021 ◽  
pp. 234094442110246
Author(s):  
Laura Andreu ◽  
Carlos Forner ◽  
José Luis Sarto
Keyword(s):  
Positive Relationship ◽  
Tracking Error ◽  
Jel Classification ◽  
Tracking Errors ◽  
Window Dressing ◽  
Future Performance ◽  
Money Flows

Using a unique database that includes publicly disclosed fund holdings at the end of the quarter as well as the holdings in all non-publicly disclosed months, we found that some funds could alter their portfolios in publicly disclosed months to artificially increase their Active Share scores and consequently appear more active and take advantage of the positive relationship between Active Share and money flows. We show how, consistent with non-informed trades, these funds erode their future performance. However, these funds reach their objective of increasing future money flows. Moreover, we find that window-dresser funds can be identified by controlling the level of tracking error. The funds with high Active Share scores and low tracking errors have the highest levels of Active Share window dressing and the worst future returns. However, compared with less active funds, they are able to capture higher money flows. JEL CLASSIFICATION G23; G11

scholarly journals Facial Feature Model for a Portrait Video Stylization

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 442 ◽  
Author(s):  
Dongxue Liang ◽  
Kyoungju Park ◽  
Przemyslaw Krompiec
Keyword(s):  
Facial Feature ◽  
Feature Model ◽  
Facial Features ◽  
Outer Face ◽  
Flow Estimation ◽  
Photorealistic Rendering ◽  
Stroke Models ◽  
The Face ◽  
Face Contour ◽  
Human Faces

With the advent of the deep learning method, portrait video stylization has become more popular. In this paper, we present a robust method for automatically stylizing portrait videos that contain small human faces. By extending the Mask Regions with Convolutional Neural Network features (R-CNN) with a CNN branch which detects the contour landmarks of the face, we divided the input frame into three regions: the region of facial features, the region of the inner face surrounded by 36 face contour landmarks, and the region of the outer face. Besides keeping the facial features region as it is, we used two different stroke models to render the other two regions. During the non-photorealistic rendering (NPR) of the animation video, we combined the deformable strokes and optical flow estimation between adjacent frames to follow the underlying motion coherently. The experimental results demonstrated that our method could not only effectively reserve the small and distinct facial features, but also follow the underlying motion coherently.

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