Novel Applications of Multimodal Biometrics

2013 ◽  
pp. 147-163
Keyword(s):  
Social Networks ◽  
Gait Recognition ◽  
System Security ◽  
Fine Tuning ◽  
Context Information ◽  
Behavioral Patterns ◽  
Multimodal Biometrics ◽  
Original Idea ◽  
Computationally Expensive ◽  
Novel Applications

This chapter presents the original idea of using social networks and context information in multimodal biometric for increased system security. A recently investigated study’s outcomes is presented, which showcase this idea as a new step in multi-biometric research. Since this method does not degrade the performance of the system and is not computationally expensive, it can be used in any biometric framework. However, as the amount of improvement depends on how distinctive and predictable people are in terms of their behavioral patterns, the method is most suitable for the predictable environments with some predefined behavioral routines. Fine tuning the system for each environment to find the most suitable parameters based on the behavioral patterns of that specific environment can result in better performance. This research is validated on example of gait recognition.

Analysis of the Performance of Eigenfaces Technique in Recognizing Non-Caucasian Faces

2012 ◽  
Vol 2 (4) ◽  
pp. 37-50
Author(s):  
Imran Khan ◽  
Sud Sudirman
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Computer Systems ◽  
System Security ◽  
Biometric Authentication ◽  
Facial Images ◽  
Detection And Recognition

Facial detection and recognition technologies are rapidly becoming an important area in many computer systems ranging from system security and biometric authentication to online social networks. However, despite of many years of research, a perfect solution to facial detection and recognition has yet not been found. As one of the earliest techniques, Eigenfaces had become one of the most popular benchmarks in this field. The technique itself, though far from providing a perfect solution, had been used by researchers to compare their proposed algorithms. The authors’ observation of the literature on and surrounding the area of facial detection and recognition found that there is a severe lack of tests and comparison of these techniques on non-Caucasian facial images. This paper aims to provide some lights into this vacuity and to assess the performance of the benchmark technique using non-Caucasian face databases

Choosing to stay away: Soccer fans’ purposeful avoidance of soccer events

2016 ◽  
Vol 28 (1) ◽  
pp. 231-246 ◽  
Author(s):  
Ilan Tamir
Keyword(s):  
Social Networks ◽  
Behavioral Patterns ◽  
Soccer Team ◽  
Behavior Based ◽  
Soccer Fans ◽  
Depth Interviews

Against conventional patterns of fandom loyalty, it is interesting to examine the behavioral patterns of enthusiastic fans who specifically choose to distance themselves from their favorite team and from reality during decisive matches. The present study explores the reasons and implications of such behavior, based on in-depth interviews with 19 soccer team fans in Israel who practice such purposeful avoidance. Findings show that such purposeful avoidance of games is generally motivated by a desire to avoid a source of stress or can be attributed to an illusion of influence, where purposeful avoidance is part of rituals whose irrationality is recognized by the fans themselves. Today, in the era of ubiquitous smartphones and social networks, purposeful avoidance becomes a true challenge.

scholarly journals Unobtrusive Behavioral and Activity-Related Multimodal Biometrics: The ACTIBIO Authentication Concept

2011 ◽  
Vol 11 ◽  
pp. 503-519 ◽  
Author(s):  
A. Drosou ◽  
D. Ioannidis ◽  
K. Moustakas ◽  
D. Tzovaras
Keyword(s):  
State Of The Art ◽  
Wide Spectrum ◽  
Gait Recognition ◽  
Biometric Recognition ◽  
Multimodal Biometrics ◽  
Physiological Profile ◽  
Security Authentication ◽  
Recognition Systems ◽  
Real Scenario ◽  
New Algorithms

Unobtrusive Authentication Using ACTIvity-Related and Soft BIOmetrics (ACTIBIO) is an EU Specific Targeted Research Project (STREP) where new types of biometrics are combined with state-of-the-art unobtrusive technologies in order to enhance security in a wide spectrum of applications. The project aims to develop a modular, robust, multimodal biometrics security authentication and monitoring system, which uses a biodynamic physiological profile, unique for each individual, and advancements of the state of the art in unobtrusive behavioral and other biometrics, such as face, gait recognition, and seat-based anthropometrics. Several shortcomings of existing biometric recognition systems are addressed within this project, which have helped in improving existing sensors, in developing new algorithms, and in designing applications, towards creating new, unobtrusive, biometric authentication procedures in security-sensitive, Ambient Intelligence environments. This paper presents the concept of the ACTIBIO project and describes its unobtrusive authentication demonstrator in a real scenario by focusing on the vision-based biometric recognition modalities.

Context-Aware Mobile Search Engine

2012 ◽  
pp. 371-385
Author(s):  
Jawad Berri ◽  
Rachid Benlamri
Keyword(s):  
Web Services ◽  
Search Engine ◽  
Information Search ◽  
Web Search ◽  
Fine Tuning ◽  
Context Information ◽  
Context Model ◽  
Mobile Web ◽  
Custom Made ◽  
Context Integration

Exploiting context information in a web search engine helps fine-tuning web services and applications to deliver custom-made information to end users. While context, including user and environment information, cannot be exploited efficiently in the wired Internet interaction type, it is becoming accessible with the mobile web where users have an intimate relationship with their handsets. In this type of interaction, context plays a significant role enhancing information search and therefore, allowing a search engine to detect relevant content in all digital forms and formats. This chapter proposes a context model and an architecture that promote integration of context information for individuals and social communities to add value to their interaction with the mobile web. The architecture relies on efficient knowledge management of multimedia resources for a wide range of applications and web services. The research is illustrated with a corporate case study showing how efficient context integration improves usability of a mobile search engine.

scholarly journals Sentiment Analysis of Short Russian Texts Using BERT and Word2Vec Embeddings

2021 ◽  
Author(s):  
Ekaterina Popova ◽  
Vladimir Spitsyn
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Social Networks ◽  
Sentiment Analysis ◽  
Deep Neural Networks ◽  
Functional Method ◽  
Fine Tuning ◽  
Machine Learning Techniques ◽  
Word Embeddings ◽  
Learning Techniques

This article is devoted to modern approaches for sentiment analysis of short Russian texts from social networks using deep neural networks. Sentiment analysis is the process of detecting, extracting, and classifying opinions, sentiments, and attitudes concerning different topics expressed in texts. The importance of this topic is linked to the growth and popularity of social networks, online recommendation services, news portals, and blogs, all of which contain a significant number of people's opinions on a variety of topics. In this paper, we propose machine-learning techniques with BERT and Word2Vec embeddings for tweets sentiment analysis. Two approaches were explored: (a) a method, of word embeddings extraction and using the DNN classifier; (b) refinement of the pre-trained BERT model. As a result, the fine- tuning BERT outperformed the functional method to solving the problem.

scholarly journals ODMBP: Behavior Forwarding for Multiple Property Destinations in Mobile Social Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Jia Xu ◽  
Jin Xin Xiang ◽  
Xiang Chen ◽  
Fang Bin Liu ◽  
Jing Jie Yu
Keyword(s):  
Social Networks ◽  
Routing Protocols ◽  
Delivery Ratio ◽  
Mobile Social Networks ◽  
Computing Model ◽  
Three Stages ◽  
Novel Applications ◽  
Behavior Profile ◽  
Behavior Profiles ◽  
Overhead Ratio

The smartphones are widely available in recent years. Wireless networks and personalized mobile devices are deeply integrated and embedded in our lives. The behavior based forwarding has become a new transmission paradigm for supporting many novel applications. However, the commodities, services, and individuals usually have multiple properties of their interests and behaviors. In this paper, we profile these multiple properties and propose an Opportunistic Dissemination Protocol based on Multiple Behavior Profile, ODMBP, in mobile social networks. We first map the interest space to the behavior space and extract the multiple behavior profiles from the behavior space. Then, we propose the correlation computing model based on the principle of BM25 to calculate the correlation metric of multiple behavior profiles. The correlation metric is used to forward the message to the users who are more similar to the target in our protocol. ODMBP consists of three stages: user initialization, gradient ascent, and group spread. Through extensive simulations, we demonstrate that the proposed multiple behavior profile and correlation computing model are correct and efficient. Compared to other classical routing protocols, ODMBP can significantly improve the performance in the aspect of delivery ratio, delay, and overhead ratio.

scholarly journals BEHAVIORAL PATTERNS IN SOCIAL NETWORKS

2014 ◽  
Vol 53 (2) ◽  
pp. 1331-1349 ◽  
Author(s):  
Anna Conte ◽  
Daniela T. Di Cagno ◽  
Emanuela Sciubba
Keyword(s):  
Social Networks ◽  
Behavioral Patterns
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