Adaptive Face Recognition of Partially Visible Faces

2012 ◽  
pp. 194-211
Author(s):  
T. Ravindra Babu ◽  
Chethan S.A. Danivas ◽  
S.V. Subrahmanya
Keyword(s):  
Face Recognition ◽  
Case Studies ◽  
Adaptive System ◽  
Research Area ◽  
Face Images ◽  
The Face ◽  
The Subject ◽  
Active Research ◽  
Partially Occluded ◽  
Active Research Area

Face Recognition is an active research area. In many practical scenarios, when faces are acquired without the cooperation or knowledge of the subject, they are likely to get occluded. Apart from image background, pose, illumination, and orientation of the faces, occlusion forms an additional challenge for face recognition. Recognizing faces that are partially visible is a challenging task. Most of the solutions to the problem focus on reconstruction or restoration of the occluded part before attempting to recognize the face. In the current chapter, the authors discuss various approaches to face recognition, challenges in face recognition of occluded images, and approaches to solve the problem. The authors propose an adaptive system that accepts the localized region of occlusion and recognizes the face adaptively. The chapter demonstrates through case studies that the proposed scheme recognizes the partially occluded faces as accurately as the un-occluded faces and in some cases outperforms the recognition using un-occluded face images.

scholarly journals Automatic Extraction of Facial Regions using CLM for the Application of Face Recognition

2020 ◽  
Vol 9 (9) ◽  
pp. 264-268
Keyword(s):  
Face Recognition ◽  
Ground Truth ◽  
Holistic Approach ◽  
Research Area ◽  
Local Approach ◽  
Person Identification ◽  
Facial Region ◽  
The Face ◽  
Active Research ◽  
Active Research Area

Facial Image processing is an active research area which involves various applications such as face detection, face recognition, person identification and also demographic information collection that is age, gender and race from the face. In general, all these applications fall under either holistic approach or local approach. In holistic approach, the whole face image is used for further processing. In local approach, the face is divided into various blocks which may contains the facial regions like eyes, eye brows, mouth, nose, cheek and chin regions. In order to develop a robust algorithm against scale, illumination, pose and expression issues, a component based or part based approaches were developed. For component based approach, the extraction of various face parts needs an automatic method to crop the facial regions closest to the manual cropping. The method of automatically extracting various facial parts is addressed in this paper. The Constrained Local Model (CLM) approach is used to identify the facial landmarks which in turn used to segregate the different facial parts. The performance of proposed approach is evaluated by ground truth of the respective facial components. The correspondence between the automatic extracted facial regions and ground truth is evaluated by SIFT descriptor. Experimental results on matching manually cropped facial regions against automatically extracted regions show that the CLM approach achieves promising performance. The extraction of various facial region will be very useful in Face recognition.

scholarly journals Three-dimensional face recognition using variance-based registration and subject-specific descriptors

2019 ◽  
Vol 16 (3) ◽  
pp. 172988141985171 ◽  
Author(s):  
Naeem Iqbal Ratyal ◽  
Imtiaz Ahmad Taj ◽  
Muhammad Sajid ◽  
Nouman Ali ◽  
Anzar Mahmood ◽  
...  
Keyword(s):  
Face Recognition ◽  
Three Dimensional ◽  
Recognition Algorithm ◽  
Superior Performance ◽  
Data Sets ◽  
Face Images ◽  
Subject Specific ◽  
The Face ◽  
The Subject ◽  
Depth Curves

Face recognition underpins numerous applications; however, the task is still challenging mainly due to the variability of facial pose appearance. The existing methods show competitive performance but they are still short of what is needed. This article presents an effective three-dimensional pose invariant face recognition approach based on subject-specific descriptors. This results in state-of-the-art performance and delivers competitive accuracies. In our method, the face images are registered by transforming their acquisition pose into frontal view using three-dimensional variance of the facial data. The face recognition algorithm is initialized by detecting iso-depth curves in a coordinate plane perpendicular to the subject gaze direction. In this plane, discriminating keypoints are detected on the iso-depth curves of the facial manifold to define subject-specific descriptors using subject-specific regions. Importantly, the proposed descriptors employ Kernel Fisher Analysis-based features leading to the face recognition process. The proposed approach classifies unseen faces by pooling performance figures obtained from underlying classification algorithms. On the challenging data sets, FRGC v2.0 and GavabDB, our method obtains face recognition accuracies of 99.8% and 100% yielding superior performance compared to the existing methods.

scholarly journals Face Recognition Using Eigen Face Based Technique Utilizing the Concept of Principal Component Analysis

2013 ◽  
Vol 10 (8) ◽  
pp. 1943-1953
Author(s):  
Prof. Samir K Bandyopadhyay ◽  
Mrs. Sunita Roy
Keyword(s):  
Principal Component Analysis ◽  
Face Recognition ◽  
Computation Time ◽  
Principal Component ◽  
Component Analysis ◽  
Research Area ◽  
Real Time System ◽  
Face Images ◽  
Small Set ◽  
Active Research

Face recognition has been an active research area since late 1980s [1]. Eigenface approach is one of the earliest appearance-based face recognition methods, which was developed by M. Turk and A. Pentland [1] in 1991. In this approach we have to perform a lots of computations, which are not feasible with respect to time in many real time system. The concept of principal component analysis (PCA) is used in this approach to reduce the dimension and hence reducing the computation time. Principal component analysis [4] decomposes face images into a small set of characteristic feature images called eigen faces.

scholarly journals Partially Occluded Face Recognition using Dynamic Time Wrapping

2018 ◽  
Vol 7 (2.22) ◽  
pp. 31 ◽  
Author(s):  
Ashish Kumar ◽  
P Shanmugavadivu
Keyword(s):  
Face Recognition ◽  
Phase I ◽  
Feature Sets ◽  
Face Images ◽  
Average Accuracy ◽  
The Face ◽  
Two Phases ◽  
Dynamic Time ◽  
Partially Occluded ◽  
Dynamic Time Wrapping

It is evident that the research contributions in the domain of partially occluded image are quite sparse. This paper presents a novel method, termed as Partially Occluded Face Recognition (POFR) using Maximally Stable External Regions (MSER) feature sets and Dynamic Time Wrapping (DTW). This proposed system works in two phases: Phase-I, creates an annotated database using the non-occluded images, and Phase-II focuses on the detection and recognition of partially occluded probe image, which is also annotated using the mechanism of phase-I. Hence, POFR selectively and dynamically calibrates the annotated database as per the annotation of the probe image. Further, the similarity between the feature sets of the annotated database images and the probe image is computed, using the principle of DTW. The POFR is tested on the face images from University of Stirling dataset and the average accuracy of face recognition is recorded as 88%. This method promises a computational advantage for partially occluded face recognition without any prior reconstruction or synthesis. The POFR finds direct applications in surveillance and security systems.  

A Person-Centered Design Framework for Serious Games for Dementia

2020 ◽  
Vol 64 (1) ◽  
pp. 18-22
Author(s):  
Bella Yigong Zhang ◽  
Mark Chignell
Keyword(s):  
Theoretical Basis ◽  
Serious Games ◽  
Aging Population ◽  
Research Area ◽  
Design Framework ◽  
Strategic Design ◽  
Health And Wellbeing ◽  
Initial Design ◽  
Active Research ◽  
Active Research Area

With the rapidly aging population and the rising number of people living with dementia (PLWD), there is an urgent need for programming and activities that can promote the health and wellbeing of PLWD. Due to staffing and budgetary constraints, there is considerable interest in using technology to support this effort. Serious games for dementia have become a very active research area. However, much of the work is being done without a strong theoretical basis. We incorporate a Montessori approach with highly tactile interactions. We have developed a person-centered design framework for serious games for dementia with initial design recommendations. This framework has the potential to facilitate future strategic design and development in the field of serious games for dementia.

Face recognition in an intelligent door lock with ResNet model based on deep learning

2021 ◽  
pp. 1-11
Author(s):  
Suphawimon Phawinee ◽  
Jing-Fang Cai ◽  
Zhe-Yu Guo ◽  
Hao-Ze Zheng ◽  
Guan-Chen Chen
Keyword(s):  
Face Recognition ◽  
Detection System ◽  
Low Cost ◽  
Ease Of Use ◽  
Raspberry Pi ◽  
Training Methods ◽  
Graphics Recognition ◽  
Face Images ◽  
The Face ◽  
Door Lock

Internet of Things is considerably increasing the levels of convenience at homes. The smart door lock is an entry product for smart homes. This work used Raspberry Pi, because of its low cost, as the main control board to apply face recognition technology to a door lock. The installation of the control sensing module with the GPIO expansion function of Raspberry Pi also improved the antitheft mechanism of the door lock. For ease of use, a mobile application (hereafter, app) was developed for users to upload their face images for processing. The app sends the images to Firebase and then the program downloads the images and captures the face as a training set. The face detection system was designed on the basis of machine learning and equipped with a Haar built-in OpenCV graphics recognition program. The system used four training methods: convolutional neural network, VGG-16, VGG-19, and ResNet50. After the training process, the program could recognize the user’s face to open the door lock. A prototype was constructed that could control the door lock and the antitheft system and stream real-time images from the camera to the app.

scholarly journals Digitization and Visualization of Folk Dances in Cultural Heritage: A Review

Inventions ◽  
2018 ◽  
Vol 3 (4) ◽  
pp. 72 ◽  
Author(s):  
Iris Kico ◽  
Nikos Grammalidis ◽  
Yiannis Christidis ◽  
Fotis Liarokapis
Keyword(s):  
Performance Evaluation ◽  
Cultural Heritage ◽  
Computer Science ◽  
Learning Process ◽  
Research Area ◽  
Active Research ◽  
Active Research Area

According to UNESCO, cultural heritage does not only include monuments and collections of objects, but also contains traditions or living expressions inherited from our ancestors and passed to our descendants. Folk dances represent part of cultural heritage and their preservation for the next generations appears of major importance. Digitization and visualization of folk dances form an increasingly active research area in computer science. In parallel to the rapidly advancing technologies, new ways for learning folk dances are explored, making the digitization and visualization of assorted folk dances for learning purposes using different equipment possible. Along with challenges and limitations, solutions that can assist the learning process and provide the user with meaningful feedback are proposed. In this paper, an overview of the techniques used for the recording of dance moves is presented. The different ways of visualization and giving the feedback to the user are reviewed as well as ways of performance evaluation. This paper reviews advances in digitization and visualization of folk dances from 2000 to 2018.

scholarly journals Enhancing Big Data Auditing

2018 ◽  
Vol 11 (1) ◽  
pp. 90
Author(s):  
Sara Alomari ◽  
Mona Alghamdi ◽  
Fahd S. Alotaibi
Keyword(s):  
Big Data ◽  
Research Area ◽  
Provable Data Possession ◽  
Integrity Verification ◽  
The Core ◽  
Outsourced Data ◽  
Active Research ◽  
Data Auditing ◽  
Active Research Area ◽  
Proof Of Retrievability

The auditing services of the outsourced data, especially big data, have been an active research area recently. Many schemes of remotely data auditing (RDA) have been proposed. Both categories of RDA, which are Provable Data Possession (PDP) and Proof of Retrievability (PoR), mostly represent the core schemes for most researchers to derive new schemes that support additional capabilities such as batch and dynamic auditing. In this paper, we choose the most popular PDP schemes to be investigated due to the existence of many PDP techniques which are further improved to achieve efficient integrity verification. We firstly review the work of literature to form the required knowledge about the auditing services and related schemes. Secondly, we specify a methodology to be adhered to attain the research goals. Then, we define each selected PDP scheme and the auditing properties to be used to compare between the chosen schemes. Therefore, we decide, if possible, which scheme is optimal in handling big data auditing.

scholarly journals E-Mail Usage in South Pacific Distance Education

2005 ◽  
pp. 1034-1039
Author(s):  
Jonathan Frank ◽  
Janet Toland ◽  
Karen D. Schenk
Keyword(s):  
Learning Styles ◽  
Research Area ◽  
Web Based ◽  
Group Interactions ◽  
Face To Face ◽  
Web Based Learning ◽  
Active Research ◽  
The Impact ◽  
E Mail ◽  
Active Research Area

The impact of cultural diversity on group interactions through technology is an active research area. Current research has found that a student’s culture appears to influence online interactions with teachers and other students (Freedman & Liu, 1996). Students from Asian and Western cultures have different Web-based learning styles (Liang & McQueen, 1999), and Scandinavian students demonstrate a more restrained online presence compared to their more expressive American counterparts (Bannon, 1995). Differences were also found across cultures in online compared to face-to-face discussions (Warschauer, 1996). Student engagement, discourse, and interaction are valued highly in “western” universities. With growing internationalization of western campuses, increasing use of educational technology both on and off campus, and rising distance learning enrollments, intercultural frictions are bound to increase.

scholarly journals Word and Chracter Segmentation in Devnagari and Odia Script – A Comparitive Analysis

2020 ◽  
Vol 9 (9) ◽  
pp. 377-382
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Research Area ◽  
Character Segmentation ◽  
National Language ◽  
Eastern India ◽  
Regional Language ◽  
Optical Character ◽  
Active Research ◽  
Active Research Area

Optical Character Recognition has been an active research area in computer science for several years. Several research works undertaken on various languages in India. In this paper an attempt has been made to find out the percentage of accuracy in word and character segmentation of Hindi (National language of India) and Odia is one of the Regional Language mostly spoken in Odisha and a few Eastern India states. A comparative article has been published under this article. 10 sets of each printed Odia and Devanagari scripts with different word limits were used in this study. The documents were scanned at 300dpi before adopting pre-processing and segmentation procedure. The result shows that the percentage of accuracy both in word and character segmentation is higher in Odia language as compared to Hindi language. One of the reasons is the use of headers line in Hindi which makes the segmentation process cumbersome. Thus, it can be concluded that the accuracy level can vary from one language to the other and from word segmentation to that of the character segmentation.

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