Advanced algorithm for gender prediction with image quality assessment

Bhaskar, Anusree; Aneesh, R P

doi:10.1109/icacci.2015.7275887

Cited by 8 publications

(4 citation statements)

References 12 publications

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“…Image quality assessment theory in liveness detection implies that there is a quality difference between fake and real images that can be detected using image quality measures which allows to build a protection method against spoofing attacks. Researchers exploited this assumption to develop various IQA techniquesin [5,[26][27][28][29][30][31][32][33]. An evaluation of several IQA techniques was done in [34].Several studies have tested the efficacy of dynamic texture analysis in liveness detection in [35][36][37][38][39][40][41][42][43].…”

Section: Texture Analysismentioning

confidence: 99%

Insight on face liveness detection: A systematic literature review

Raheem¹,

Ahmad²,

Adnan³

2019

IJECE

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<p>To review researcher’s attempts in response to the problem of spoofing and liveness detection, mapping the research overview from the literature survey into a suitable taxonomy, exploring the basic properties of the field, motivation of using liveness detection methods in face recognition, and Problems that may restrain the advantages. We presented a subjected search on face recognition with liveness detection and its synonyms in four main databases: Web of science, Science Direct, Scopus and IEEE Xplore. We believe that these databases are widely inclusive enough to cover the literature.<em> </em>The final number of articles considered is 65 articles. 4 of them where review and survey articles that described a general overview about liveness detection and anti-spoofing methods. Since 2012, and despite of leaving some areas unestablished and needs more attention, researchers tried to keep track of liveness detection in several ways. No matter what their category is, articles concentrated on challenges that faces the full utility of anti-spoofing methods and recommended some solutions to overcome these challenges. In this paper, different types of liveness detection and face anti-spoofing techniques are investigated to keep researchers updated with what is being developed in this field.</p>

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Section: Texture Analysismentioning

confidence: 99%

Insight on face liveness detection: A systematic literature review

Raheem¹,

Ahmad²,

Adnan³

2019

IJECE

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“…Once again, the majority of gender prediction papers concern the analysis of facial data (e.g. see [47,[109][110][111][112][113][114][115]). The main focus of these studies is the use of PCA for object identification on the faces and SVM for gender classification.…”

Section: Gender Predictionmentioning

confidence: 99%

Predictive biometrics: a review and analysis of predicting personal characteristics from biometric data

Fairhurst

Abreu

2017

IET biom.

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Interest in the exploitation of soft biometrics information has continued to develop over the last decade or so. In comparison with traditional biometrics, which focuses principally on person identification, the idea of soft biometrics processing is to study the utilisation of more general information regarding a system user, which is not necessarily unique. There are increasing indications that this type of data will have great value in providing complementary information for user authentication. However, the authors have also seen a growing interest in broadening the predictive capabilities of biometric data, encompassing both easily definable characteristics such as subject age and, most recently, 'higher level' characteristics such as emotional or mental states. This study will present a selective review of the predictive capabilities, in the widest sense, of biometric data processing, providing an analysis of the key issues still adequately to be addressed if this concept of predictive biometrics is to be fully exploited in the future.

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“…Michele, Liangliang and John [14] proposed a method to extract gender information from the pictures posted in social media feeds and achieved 88% mean accuracy; Dileep M R and Ajit Danti [9] proposed an effective method named Multiple Hierarchical decision based on Neural Networks to predict human age and gender from facial images. Fake biometric identifiers can be of the form where one person imitates as another, so Anusree Bhaskar [10] presented a software based multi-biometric system to classify real and fake face samples and gender classification. With AR face database, Qingqing Lu, Jianfeng Lu and Dongjun Yu [11] build a convolutional neural network for gender classification based on facial image.…”

Section: 3gender Predictionmentioning

confidence: 99%

“…The difficulty in classifying men and women in retail scenario raises an interesting research question: Can we inference users' gender automatically only based on their purchase behaviors and other known external factors? Although some recent studies suggest that gender attributes are predictable from different behavioral data, such as linguistics writing [5,6,7,8], facial images [9,10,11], social media [12,13,14] and mobile data [15] to our best knowledge, seldom practice has been conducted on purchase behaviors in retail scenario.…”

Section: Introductionmentioning

confidence: 99%

Gender Prediction of Consumers Using Offline Purchase Data

Ji¹

2018

Proceedings of the 2017 4th International Conference on Machinery, Materials and Computer (MACMC 2017)

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Demographic attributes such as gender of consumers provide important in-formation for marketing, personalization, and user behavior research. With the growing necessity for gender information in personalized intelligent systems, gender prediction of consumers has become an important research issue. This paper addresses the problem of predicting consumers' gender based on purchase data and some external factors, such as weather and name. According to the characteristics of offline data, we compared the performance of different algorithms and the contribution of different features to gender prediction was compared. From the experiments conducted on real-world datasets, we found the most important features and the best performing algorithms that influenced the gender prediction of offline purchase da-ta. This study provided suggestions for apparel offline markets to develop effective marketing strategies to reach their target market, for consumer educators and for educators in the retail merchandizing area to prepare their students for future careers.

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Advanced algorithm for gender prediction with image quality assessment

Abstract: Forged biometric systems are a crucial

Cited by 8 publications

References 12 publications

Insight on face liveness detection: A systematic literature review

Insight on face liveness detection: A systematic literature review

Predictive biometrics: a review and analysis of predicting personal characteristics from biometric data

Gender Prediction of Consumers Using Offline Purchase Data

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