scholarly journals An Overview of Multimodal Biometrics Using the Face and Ear

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Yichao Ma ◽  
Zengxi Huang ◽  
Xiaoming Wang ◽  
Kai Huang

In the recent years, we have witnessed the rapid development of face recognition, though it is still plagued by variations such as facial expressions, pose, and occlusion. In contrast to the face, the ear has a stable 3D structure and is nearly unaffected by aging and expression changes. Both the face and ear can be captured from a distance and in a nonintrusive manner, which makes them applicable to a wider range of application domains. Together with their physiological structure and location, the ear can readily serve as supplement to the face for biometric recognition. It has been a trend to combine the face and ear to develop nonintrusive multimodal recognition for improved accuracy, robustness, and security. However, when either the face or the ear suffers from data degeneration, if the fusion rule is fixed or with inferior flexibility, a multimodal system may perform worse than the unimodal system using only the modality with better quality sample. The biometric quality-based adaptive fusion is an avenue to address this issue. In this paper, we present an overview of the literature about multimodal biometrics using the face and ear. All the approaches are classified into categories according to their fusion levels. In the end, we pay particular attention to an adaptive multimodal identification system, which adopts a general biometric quality assessment (BQA) method and dynamically integrates the face and ear via sparse representation. Apart from a refinement of the BQA and fusion weights selection, we extend the experiments for a more thorough evaluation by using more datasets and more types of image degeneration.

2019 ◽  
Vol 4 (91) ◽  
pp. 21-29 ◽  
Author(s):  
Yaroslav Trofimenko ◽  
Lyudmila Vinogradova ◽  
Evgeniy Ershov

Author(s):  
Marc J. Stern

Chapter 9 contains five vignettes, each based on real world cases. In each, a character is faced with a problem and uses multiple theories within the book to help him or her develop and execute a plan of action. The vignettes provide concrete examples of how to apply the theories in the book to solving environmental problems and working toward environmental sustainability in a variety of contexts, including managing visitors in a national park, developing persuasive communications, designing more collaborative public involvement processes, starting up an energy savings program within a for-profit corporation, and promoting conservation in the face of rapid development.


2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1029.1-1029
Author(s):  
Y. Livshits ◽  
O. Teplyakova ◽  
A. Sarapulova

Background:Telemedicine counseling (TMC) has gained rapid development during the COVID-19 pandemic. The prospect of using this technology in rheumatology was based on the possibility of getting maximum information about the patient during the survey, examination and interpretation of laboratory and instrumental data, that is excepting direct contact with the patient. Several rheumatological clinics have reported on the success of using TMC. However, there is very little data of the difficulties that can be encountered when organizing this process.Objectives:To characterize the identified problems during TMC in rheumatology, to suggest potential directions for their elimination.Methods:Since June 2021, on the basis of the Medical Association “New Hospital”, Yekaterinburg, Russian Federation, 76 TMCs have been performed on the profile of rheumatology in patients aged 29 to 71 years. Of these, 13 applied to the primary TMC, the other patients were preliminarily examined in person. The consultation included the preliminary acquaintance with the examination results, a 20-minute video communication and writing of a conclusion. After each TMC, a survey was conducted between the doctor and the patient, including the identified deficiencies in counseling. The frequency of identified problems is presented as an absolute indicator and as a percentage of the total number of TMCs performed.Results:We noted a high degree of patient satisfaction: 74 (97.4%) responded that they received answers to all. However, according to the doctor, the following groups of problems were identified.[1]Technical problems in 29 (38.2%): most often there were various problems with the Internet, but there were also registered: the end of the charge on the patient’s tablet, the patient was not registered in the electronic queue. Elimination of these violations depends on the work of IT-specialists, but each consulting physician should be prepared for an immediate transition to an alternative form of communication (for example - telephone).[2]Lack of objective examination, leading to the impossibility of correct remote diagnosis - 8 (10.5%). This problem was identified due to the inability to establish the presence or absence of arthritis during the initial diagnosis (6 cases) and to clarify the nature of the rash (2 cases). All patients are invited for a face-to-face consultation.[3]The need to write prescriptions for psychotropic drugs - 12 (15.8%), which under the conditions of national legislation cannot be done in the TMC regime.[4]The time spent directly on remote communication with the patient was 17.2 minutes (from 8 to 31), however, taking into account the study data and writing the conclusion, the total time was 40.7 minutes (from 21 to 73). Thus, it turned out that the average time for remote and face-to-face consultations is the same, while TMC’s payment is only about 50% of the face-to-face consultation. This situation reduces the doctor’s interest in carrying out TMC. The solution to the problem is associated with reducing the time for the documentation process through technical improvements. In addition, of the 9 patients in whom the TMC process lasted 60 minutes or more, 5 were diagnosed with fibromyalgia. It is possible that with a previously established diagnosis of fibromyalgia, only face-to-face counseling should be recommended to patients.Conclusion:The TMC system is promising, however, there are a number of problems that need to be improved, since they can reduce the doctor’s interest in using this technology.Disclosure of Interests:None declared


2021 ◽  
Author(s):  
Molly Kozminsky ◽  
Thomas Carey ◽  
Lydia L. Sohn

Lipid-based nanoparticles have risen to the forefront of the COVID-19 pandemic—from encapsulation of vaccine components to modeling the virus, itself. Their rapid development in the face of the volatile nature of the pandemic requires high-throughput, highly flexible methods for characterization. DNA-directed patterning is a versatile method to immobilize and segregate lipid-based nanoparticles for subsequent analysis. DNA-directed patterning selectively conjugates oligonucleotides onto a glass substrate and then hybridizes them to complementary oligonucleotides tagged to the liposomes, thereby patterning them with great control and precision. The power of this method is demonstrated by characterizing a novel recapitulative lipid-based nanoparticle model of SARS-CoV-2 —S-liposomes— which present the SARS-CoV-2 spike (S) protein on their surfaces. Patterning of a mixture of S-liposomes and liposomes that display the tetraspanin CD63 into discrete regions of a substrate is used to show that ACE2 specifically binds to S-liposomes. Importantly, DNA-directed patterning of S-liposomes is used to verify the performance of a commercially available neutralizing antibody against the S protein. Ultimately, the introduction of S-liposomes to ACE2-expressing cells demonstrates the biological relevance of DNA-directed patterning. Overall, DNA-directed patterning enables a wide variety of custom assays for the characterization of any lipid-based nanoparticle.


Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5523 ◽  
Author(s):  
Nada Alay ◽  
Heyam H. Al-Baity

With the increasing demand for information security and security regulations all over the world, biometric recognition technology has been widely used in our everyday life. In this regard, multimodal biometrics technology has gained interest and became popular due to its ability to overcome a number of significant limitations of unimodal biometric systems. In this paper, a new multimodal biometric human identification system is proposed, which is based on a deep learning algorithm for recognizing humans using biometric modalities of iris, face, and finger vein. The structure of the system is based on convolutional neural networks (CNNs) which extract features and classify images by softmax classifier. To develop the system, three CNN models were combined; one for iris, one for face, and one for finger vein. In order to build the CNN model, the famous pertained model VGG-16 was used, the Adam optimization method was applied and categorical cross-entropy was used as a loss function. Some techniques to avoid overfitting were applied, such as image augmentation and dropout techniques. For fusing the CNN models, different fusion approaches were employed to explore the influence of fusion approaches on recognition performance, therefore, feature and score level fusion approaches were applied. The performance of the proposed system was empirically evaluated by conducting several experiments on the SDUMLA-HMT dataset, which is a multimodal biometrics dataset. The obtained results demonstrated that using three biometric traits in biometric identification systems obtained better results than using two or one biometric traits. The results also showed that our approach comfortably outperformed other state-of-the-art methods by achieving an accuracy of 99.39%, with a feature level fusion approach and an accuracy of 100% with different methods of score level fusion.


2018 ◽  
Vol 7 (3.34) ◽  
pp. 237
Author(s):  
R Aswini Priyanka ◽  
C Ashwitha ◽  
R Arun Chakravarthi ◽  
R Prakash

In scientific world, Face recognition becomes an important research topic. The face identification system is an application capable of verifying a human face from a live videos or digital images. One of the best methods is to compare the particular facial attributes of a person with the images and its database. It is widely used in biometrics and security systems. Back in old days, face identification was a challenging concept. Because of the variations in viewpoint and facial expression, the deep learning neural network came into the technology stack it’s been very easy to detect and recognize the faces. The efficiency has increased dramatically. In this paper, ORL database is about the ten images of forty people helps to evaluate our methodology. We use the concept of Back Propagation Neural Network (BPNN) in deep learning model is to recognize the faces and increase the efficiency of the model compared to previously existing face recognition models.   


2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Zheng-Yang Chen ◽  
Song Guo ◽  
Bin-Bin Li ◽  
Nan Jiang ◽  
Ao Li ◽  
...  

With the rapid development of modern medical technology and the deterioration of living environments, cancer, the most important disease that threatens human health, has attracted increasing concerns. Although remarkable achievements have been made in tumor research during the past several decades, a series of problems such as tumor metastasis and drug resistance still need to be solved. Recently, relevant physiological changes during space exploration have attracted much attention. Thus, space exploration might provide some inspiration for cancer research. Using on ground different methods in order to simulate microgravity, structure and function of cancer cells undergo many unique changes, such as cell aggregation to form 3D spheroids, cell-cycle inhibition, and changes in migration ability and apoptosis. Although numerous better experiments have been conducted on this subject, the results are not consistent. The reason might be that different methods for simulation have been used, including clinostats, random positioning machine (RPM) and rotating wall vessel (RWV) and so on. Therefore, we review the relevant research and try to explain novel mechanisms underlying tumor cell changes under weightlessness.


1982 ◽  
Vol 15 (3) ◽  
pp. 211-239 ◽  
Author(s):  
John Henry

In spite of vigorous opposition by a number of historians it has now become a commonplace that the rapid development of the ‘new philosophy’ sprang from the ideology of Puritanism. What began its career as the ‘Merton thesis’ has now been refined, developed, and so often repeated that it seems to be almost unassailable. However, the two foremost historians in the entrenchment of this new orthodoxy are willing, in principle, to concede that ‘in reality things were very mixed up’, and that non-Puritan natural philosophers at the time were operating ‘in a precisely similar manner’ to their Puritan contemporaries. Indeed, it would be impossible not to concede this in the face of the many critiques launched against the Merton thesis.


Author(s):  
K. V. Usha Ramani

One of the crucial difficulties we aim to find in computer vision is to recognize items automatically without human interaction in a picture. Face detection may be seen as an issue when the face of human beings is detected in a picture. The initial step towards many face-related technologies, including face recognition or verification, is generally facial detection. Face detection however may be quite beneficial. A biometric identification system besides fingerprint and iris would likely be the most effective use of face recognition. The door lock system in this project consists of Raspberry Pi, camera module, relay module, power input and output, connected to a solenoid lock. It employs the two different facial recognition algorithms to detect the faces and train the model for recognition purpose


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