PERFORMANCE ANALYSIS BETWEEN KEYPOINT OF SURF AND SKIN COLOUR YCBCR BASED TECHNIQUE FOR FACE DETECTION AMONG FINAL YEAR UTEM MALE STUDENT

2017 ◽  
Vol 79 (5-2) ◽  
Author(s):  
Mohd Safirin Karis ◽  
Nursabillilah Mohd Ali ◽  
Wira Hidayat Mohd Saad ◽  
Amar Faiz Zainal Abidin ◽  
Nazurah Ismaun ◽  
...  
Keyword(s):  
Face Detection ◽  
Male Student ◽  
Feature Point ◽  
Skin Colour ◽  
Face Area ◽  
Project Analysis ◽  
Significant Difference ◽  
Out Of Plane ◽  
The Face ◽  
Colour Extract

This project presents an analysis of development out-of-plane of face detection using Speeded-Up Robust Feature (SURF) and skin colour of YCbCr colour-based technique. The technique of SURF method and skin colour of YCbCr was explored in order to compare the performances in terms of time response. The significant difference can be seen with an extraction of feature point followed by matching it using SURF technique whereas skin colour of YCbCr colour extract the skin region. It is discovered that the skin colour of the respondent does not give any impact on the result. The outcome is presented using MATLAB 2013a software. To determine the response of both technique in detecting the face area, out-of-plane captured images is varied and chosen randomly from 0°, 45° and 90°. The outcome shows that SURF technique can detect the SURF feature point in different angles, but the matching point cannot discover if the images in 45° and 90°. In contrast, the skin colour of YCbCr can spot the present of face despite its angle. Through the project analysis, the respondents’ tone of skin colour does not affect the result of both techniques. Overall, SURF technique gives an impact in face detection if the angle of the images is being varied. Different angles are applied in this technique in order to vary the result of out-of-plane. The number of key feature for image 2 is the highest due to variation of angles from 90°, 45° and 0° in corresponding.

scholarly journals Real-Time Pre-Identification and Cascaded Detection for Tiny Faces

2019 ◽  
Vol 9 (20) ◽  
pp. 4344 ◽  
Author(s):  
Yang ◽  
Li ◽  
Min ◽  
Wang
Keyword(s):  
Real Time ◽  
Face Detection ◽  
Region Of Interest ◽  
Detection Methods ◽  
Time Performance ◽  
Face Area ◽  
The Face ◽  
Two Stages ◽  
Coarse To Fine ◽  
Identification Mechanism

Although the face detection problem has been studied for decades, searching tiny faces in the whole image is still a challenging task, especially in low-resolution images. Traditional face detection methods are based on hand-crafted features, but the features of tiny faces are different from those of normal-sized faces, and thus the detection robustness cannot be guaranteed. In order to alleviate the problem in existing methods, we propose a pre-identification mechanism and a cascaded detector (PMCD) for tiny-face detection. This pre-identification mechanism can greatly reduce background and other irrelevant information. The cascade detector is designed with two stages of deep convolutional neural network (CNN) to detect tiny faces in a coarse-to-fine manner, i.e., the face-area candidates are pre-identified as region of interest (RoI) based on a real-time pedestrian detector and the pre-identification mechanism, the set of RoI candidates is the input of the second sub-network instead of the whole image. Benefiting from the above mechanism, the second sub-network is designed as a shallow network which can keep high accuracy and real-time performance. The accuracy of PMCD is at least 4% higher than the other state-of-the-art methods on detecting tiny faces, while keeping real-time performance.

scholarly journals Computerized Face Detection and Tracking

2019 ◽  
Vol 8 (12) ◽  
pp. 2800-2802 ◽  
Keyword(s):  
Face Detection ◽  
Basic Research ◽  
Joint Effort ◽  
The Past ◽  
Face Area ◽  
Detection And Tracking ◽  
Target Article ◽  
The Face ◽  
Testing Issue ◽  
Human Faces

Item revelation has been an unprecedented test from the past couple of years. In PC vision human face area is a basic research topic. It is required for some PC applications like HCI, perception, human-robot joint effort, etc. In this field facial following is finding greater advancement of use in security and prosperity applications to recognize distinctive situations1 . This following zone can be used to control or talk with robots. Perceiving human faces in a video is a fantastic testing issue. These setups may take after edge of view, establishment control, and diverse edifications. This is a result of high variety of setups that may occur. The multifaceted idea of the face results in a particular dimension of issue for speedy area and following. In this paper we use two philosophies for recognizing a face and track it always. In a general sense video groupings give a larger number of information than a still picture. It is reliably a testing undertaking to pursue a target thing in a live video. We experience challenges like edification; present assortment and hindrance in pre-planning stages. In any case, this is can be overpowered by disclosure of the target article unendingly in each and every edge. Face following by Kanade Lucas Tomasi computation that is used to pursue face reliant on arranged features.Automatic face detection and tracking is a challenging part and here the proposed method is improvised on that.

Human Face Detection Method Based on Skin Color Model

2013 ◽  
Vol 706-708 ◽  
pp. 1877-1881
Author(s):  
San Tang
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Detection Method ◽  
Color Space ◽  
Color Model ◽  
Knowledge Based ◽  
Face Area ◽  
The Face ◽  
Skin Color Model ◽  
Active Research

Face detection is the first step of face recognition, and is a very active research topic in the filed of computer vision and pattern recognition. A skin color model based face detection method for chromatic images is proposed in this paper. The H-CgCr skin color model is established by taking advantage of the color pixels clustering distribution in the HSV and YCgCr color space. The noises are eliminated based on skin color segmentation, and the face candidate region is judged according to knowledge-based, finally, the position of the face area is marked by the box. The experimental results demonstrate that the proposed method is feasible and effective.

scholarly journals EFEKTIVITAS NATURAL FACE MASK DALAM MENINGKATKAN KELEMBABAN KULIT WAJAH

2019 ◽  
Vol 7 (3) ◽  
pp. 138
Author(s):  
Swaidatul Masluhiya AF ◽  
Hasminar Rachman Fidiastuti
Keyword(s):  
Face Mask ◽  
Significance Test ◽  
Water Evaporation ◽  
Dry Skin ◽  
Black Cumin ◽  
Face Area ◽  
Significant Difference ◽  
The Face ◽  
The Government ◽  
Skin Moisture

This study aimed to determine the effect of using natural masks to moisturize dry skin. This natural mask was made of ingredients that are safe to use and based on special formulations which include; bengkoang powder (2 grams), chocolate powder (1 gram), black cumin oil (0.6 ml), and honey (5 ml). This formulation was made so that the resultied mask formed paste stucture that can be directly applied. Masks were given to ten probandal women who have dry skin types and are 30-40 years old. Masks were used twice / week for six weeks (12 times usage). The instrument used to measure the moisture level of facial skin was a skin analyzer (HL-611) by directly attaching it to the face area and the results can be seen after 4-5 seconds. The data were analysed using ANOVA test 95% confidence interval and significance test using SPSS 15 for windows. The results showed that skin moisture values increased around 3.9% within 6 weeks of use, with a 0.8% increase at week 2, at week 4 there was an increase of 1.65% and at week 6 there was an increase in skin moisture by 1.4%. The moisture value of the skin on the face area (forehead, nose, chin, cheeks) showed no significant difference with almost the same value of humidity. It is recommended for dry skin types to use a face mask that contains oil as a skin lubricant and to protect water evaporation from the skin. It is necessary to do further testing on this natural mask so that safety on the skin can be guaranteed. It needs to be done so that the final product obtained meets the face mask safety quality standards set by the government. Keywords: Bengkuang; cocoa; black cumin; honey; natural mask.

Face detection in single and multiple images using different skin color models

2020 ◽  
Vol 13 ◽  
Author(s):  
Manpreet Kaur ◽  
Jasdev Bhatti ◽  
Mohit Kumar Kakkar ◽  
Arun Upmanyu
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Input Image ◽  
Morphological Operations ◽  
Reliability Model ◽  
Multiple Images ◽  
Face Region ◽  
Bounding Box ◽  
The Face ◽  
Precision And Accuracy

Introduction: Face Detection is used in many different steams like video conferencing, human-computer interface, in face detection, and in the database management of image. Therefore, the aim of our paper is to apply Red Green Blue ( Methods: The morphological operations are performed in the face region to a number of pixels as the proposed parameter to check either an input image contains face region or not. Canny edge detection is also used to show the boundaries of a candidate face region, in the end, the face can be shown detected by using bounding box around the face. Results: The reliability model has also been proposed for detecting the faces in single and multiple images. The results of the experiments reflect that the algorithm been proposed performs very well in each model for detecting the faces in single and multiple images and the reliability model provides the best fit by analyzing the precision and accuracy. Moreover Discussion: The calculated results show that HSV model works best for single faced images whereas YCbCr and TSL models work best for multiple faced images. Also, the evaluated results by this paper provides the better testing strategies that helps to develop new techniques which leads to an increase in research effectiveness. Conclusion: The calculated value of all parameters is helpful for proving that the proposed algorithm has been performed very well in each model for detecting the face by using a bounding box around the face in single as well as multiple images. The precision and accuracy of all three models are analyzed through the reliability model. The comparison calculated in this paper reflects that HSV model works best for single faced images whereas YCbCr and TSL models work best for multiple faced images.

Self perceived oro-facial behaviour and malocclusion among young adults in Hyderabad city

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Dasari Tejaswini ◽  
Suhas Kulkarni ◽  
Dolar Doshi ◽  
Adepu Srilatha
Keyword(s):  
Gender Differences ◽  
Young Adults ◽  
Health Knowledge ◽  
Simple Random Sampling ◽  
Cross Sectional Study ◽  
Sampling Procedure ◽  
Cross Sectional ◽  
Significant Difference ◽  
The Face ◽  
The Impact

AbstractBackgroundAesthetic alterations in the face can be self-perceived and can affect quality of life in young adults.ObjectiveTo assess the impact of malocclusion on self- perceived oro-facial behaviour among young adults.MethodsA Cross sectional study was conducted among 638 young adults (aged 18–21 years) of Hyderabad city. One college from each of the five zones of the Hyderabad city (five colleges) were selected by simple random sampling procedure. A 21-item Oro-facial investment scale (OFIS) questionnaire assessing self-perceived oral health knowledge, attitude, practice and Dental Aesthetic Index (DAI) assessing the severity of malocclusion was used. Data were analysed with standard statistical software (SPSS, Statistical package for the social sciences, version 20.0). p < 0.05 was considered statistically significant.ResultsMales had higher mean scores for knowledge (2.90 ± 0.49) than females (2.73 ± 0.82) and was statistically significant (p = 0.002*). No statistically significant gender differences were found in relation to attitude and practice. Analysis of variance (ANOVA) showed that there was a significant difference in all the three scores (knowledge, attitude, practice) with respect to age, with significantly high score for knowledge and practice among 18 year old subjects (p = 0.0001*; p = 0.0003* respectively) and attitude among 21 year old subjects (p = 0.0049*). No statistically significant age, gender differences were found in relation to DAI scores. Upon correlation, DAI significantly and positively correlated with knowledge (p = 0.03*) and attitude (p = 0.0001*).ConclusionThis study has shown significant impact of malocclusion on the self-perceived oro-facial behaviour.

scholarly journals COVD-26. TELEPHONE CONSULTATIONS IN NEURO-ONCOLOGY DURING THE COVID-19 PANDEMIC: LEVELS OF PATIENT SATISFACTION AND COMPARISON WITH TRADITIONAL FACE-TO-FACE CONSULTATIONS

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii26-ii26
Author(s):  
Emma Toman ◽  
Claire Goddard ◽  
Frederick Berki ◽  
William Garratt ◽  
Teresa Scott ◽  
...  
Keyword(s):  
Patient Satisfaction ◽  
University Hospitals ◽  
Health Crisis ◽  
Patient Satisfaction Questionnaire ◽  
Telephone Consultation ◽  
Exact Test ◽  
Face To Face ◽  
Significant Difference ◽  
The Face ◽  
The University

Abstract INTRODUCTION Controversy exists as to whether telephone clinics are appropriate in neurosurgical-oncology. The COVID-19 pandemic forced neuro-oncology services worldwide to re-design and at the University Hospitals Birmingham UK, telephone clinics were quickly implemented in select patients to limit numbers of patients attending hospital. It was important to determine how these changes were perceived by patients. METHODS A 20-question patient satisfaction questionnaire was distributed to patients who attended neuro-oncology clinic in person (“face-to-face”), or via the telephone. Fisher’s exact test was used to determine significance, which was set at p&lt; 0.05. RESULTS Eighty questionnaires were distributed between June 2020 and August 2020. Overall, 50% (n=40) of patients returned the questionnaire, 50% (n=23) of face-to-face and 50% (n=17) telephone patients. Of those who received telephone consultations, 88% (n=15) felt the consultation was convenient, 88% (n=15) were satisfied with their consultation and 18% (n=3) felt they would have preferred to have a face-to-face appointment. Of those who attended clinic in person, 96% (n=22) felt their consultation was convenient, 100% (n=23) were satisfied with their consultation and 13% (n=3) would have preferred a telephone consultation. Within the face-to-face clinic attendees, only 13% (n=3) were concerned regarding the COVID risk associated with attending hospital. There was no significant difference in patient convenience or satisfaction (p=0.565 and p=0.174 respectively) between face-to-face and telephone clinics. There was no significant difference in whether patients would’ve preferred the alternative method of consultation (p &gt; 0.999). CONCLUSION Our study suggests that careful patient selection for neuro-oncology telephone clinic is not inferior to face-to-face clinic. Telephone clinic during COVID-19 pandemic proved to be convenient, safe and effective. This global health crisis has transformed telephone neuro-oncology consultations from an experimental innovation into established practice and should be continued beyond the pandemic in select cases.

Performance Analysis of GPU-CPU for The Face Detection

2021 ◽  
Author(s):  
Dolly Indra ◽  
Ramdan Satra ◽  
Muhammad Jamil Asshiddiq ◽  
Lukman Syafie ◽  
Erick Irawadi Alwi ◽  
...  
Keyword(s):  
Performance Analysis ◽  
Face Detection ◽  
The Face

Face Image Segmentation Using Color Information and Saliency Map

2011 ◽  
Vol 55-57 ◽  
pp. 77-81
Author(s):  
Hui Ming Huang ◽  
He Sheng Liu ◽  
Guo Ping Liu
Keyword(s):  
Image Segmentation ◽  
Human Skin ◽  
Skin Color ◽  
Saliency Map ◽  
Face Image ◽  
Color Information ◽  
Attention Model ◽  
Face Area ◽  
Face Region ◽  
The Face

In this paper, we proposed an efficient method to address the problem of color face image segmentation that is based on color information and saliency map. This method consists of three stages. At first, skin colored regions is detected using a Bayesian model of the human skin color. Then, we get a chroma chart that shows likelihoods of skin colors. This chroma chart is further segmented into skin region that satisfy the homogeneity property of the human skin. The third stage, visual attention model are employed to localize the face region according to the saliency map while the bottom-up approach utilizes both the intensity and color features maps from the test image. Experimental evaluation on test shows that the proposed method is capable of segmenting the face area quite effectively，at the same time, our methods shows good performance for subjects in both simple and complex backgrounds, as well as varying illumination conditions and skin color variances.

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