Face recognition for smart environments

Smart environments, wearable computers, and ubiquitous computing in general are the coming “fourth generation” of computing and information technology. But that technology will be a stillbirth without new interfaces for interaction, minus a keyboard or mouse. To win wide consumer acceptance, these interactions must be friendly and personalized; the next generation interfaces must recognize people in their immediate environment and, at a minimum, know who they are. In this article, the authors discuss face recognition technology, how it works, problems to be overcome, current technologies, and future developments and possible applications. Twenty years ago, the problem of face recognition was considered among the most difficult in artificial intelligence and computer vision. Today, however, there are several companies that sell commercial face recognition software that is capable of high-accuracy recognition with databases of more than 1,000 people. The authors describe the face recognition technology used, explaining the algorithms for face recognition as well as novel applications, such as behavior monitoring that assesses emotions based on facial expressions     

Human interaction with IoT-based smart environments

This paper describes concepts, design, implementation, and performance evaluation of a 3D-based user interface for accessing IoT-based Smart Environments (IoT-SE). The generic interaction model of the described work addresses some major challenges of Human-IoT-SE-Interaction such as cognitive overload associated with manual device selection in complex IoT-SE, loss of user control, missing system image or over-automation. To address these challenges we propose a 3D-based mobile interface for mixed-initiative interaction in IoT-SE. The 3D visualization and 3D UI, acting as the central feature of the system, create a logical link between physical devices and their virtual representation on the end user’s mobile devices. By so doing, the user can easily identify a device within the environment based on its position, orientation, and form, and access the identified devices through the 3D interface for direct manipulation within the scene. This overcomes the problem of manual device selection. In addition, the 3D visualization provides a system image for the IoT-SE, which supports users in understanding the ambience and things going on in it. Furthermore, the mobile interface allows users to control the amount and the way the IoT-SE automates the environment. For example, users can stop or postpone system triggered automatic actions, if they don’t like or want them. Users also can remove a rule forever. By so doing, users can delete smart behaviors of their IoT-SE. This helps to overcome the automation challenges. In this paper, we present the design, implementation and evaluation of the proposed interaction system. We chose smart meeting rooms as the context for prototyping and evaluating our interaction concepts. However, the presented concepts and methods are generic and could be adapted to similar environments such as smart homes. We conducted a subjective usability evaluation (ISO-Norm 9241/110) with 16 users. All in one the study results indicate that the proposed 3D-User Interface achieved a good high score according to the ISO-Norm scores.     

Designing smart artifacts for smart environments

Smart artifacts promise to enhance the relationships among participants in distributed working groups, maintaining personal mobility while offering opportunities for the collaboration, informal communication, and social awareness that contribute to the synergy and cohesiveness inherent in collocated teams. Two complementary trends have resulted in the creation of smart environments that integrate information, communication, and sensing technologies into everyday objects. We distinguish between two types of smart artifacts: system-oriented, importunate smartness and people-oriented, empowering smartness. The system-oriented and people-oriented approaches represent the end points of a line along which we can position weighted combinations of both types of smartness depending on the application domain. We developed the Hello.Wall, our version of an ambient display, for the Ambient Agoras environment. The Hello.Wall transmits organization-oriented information publicly and information addressed to individuals privately.     

Bahrain issues biometric smart ID card tender

The Kingdom of Bahrain is planning a new national ID card based on multi-application smart cards, PKI and biometrics. The country’s Central Informatics Organisation has issued a ‘request for tender’ that highlights the extent of the ambitious project. The card may be used as a driving licence, for health data, for immigration and as an e-purse, as well as for ID. It can also be used for fast tracking through Bahrain International Airport, using fingerprint technology to authenticate passengers at two dedicated access gates (one in arrivals, one in departures).This is a short news story only. Visit www.compseconline.com for the latest computer security news.     

Task sensitivity in EEG biometric recognition

This work explores the sensitivity of electroencephalographic-based biometric recognition to the type of tasks required by subjects to perform while their brain activity is being recorded. A novel wavelet-based feature is used to extract identity information from a database of 109 subjects who performed four different motor movement/imagery tasks while their data were recorded. Training and test of the system was performed using a number of experimental protocols to establish if training with one type of task and tested with another would significantly affect the recognition performance. Also, experiments were conducted to evaluate the performance when a mixture of data from different tasks was used for training. The results suggest that performance is not significantly affected when there is a mismatch between training and test tasks. Furthermore, as the amount of data used for training is increased using a combination of data from several tasks, the performance can be improved. These results indicate that a more flexible approach may be incorporated in data collection for EEG-based biometric systems which could facilitate their deployment and improved performance.     

Location-aware communications in smart environments

We present a location-aware communication approach for smart home environments that is based on a symbolic location model that represents the containment relationships between physical objects, computing devices, and places. The approach enables people and devices to discover and connect with communication partners based on their co-locations. It also provides non-smart objects, including home appliances, everyday objects, and places, with virtual counterparts, which both represent them and work as proxies for their targets. We present the design for this approach and describe its implementation and applications.     

EEG signal preprocessing for biometric recognition

Electroencephalography (EEG) has been recently investigated as a biometric modality for automatic people recognition purposes. Several studies have shown that brain signals possess subject-specific traits that allow distinguishing people. Nonetheless, extracting discriminative characteristics from EEG recordings may be a challenging task, due to the significant presence of artifacts in the acquired data. In order to cope with such issue, in this paper we evaluate the effectiveness of some preprocessing techniques in automatically removing undesired EEG contributions, with the aim of improving the achievable recognition rates. Specifically, methods based on blind source separation and sample entropy estimation are here investigated. An extensive set of experimental tests, performed over a large database comprising recordings taken from 50 healthy subjects during three distinct sessions spanning a period of about one month, in both eyes-closed and eyes-open conditions, is carried out to analyze the performance of the proposed approaches.     

生物特征识别技术在金融卡行业中的应用

介绍了目前全球范围内的几种生物识别技术及其识别过程。在此基础上,介绍了我国的生物特征识别系统。为提高金融卡使用时的简洁和高效,提出将生物特征数据集成到银行IC卡上,做到一卡一人使用,这对我国目前进行的金融卡EMV大迁移有着重大的意义。     

Mixed reality participants in smart meeting rooms and smart home environments

Human–computer interaction requires modeling of the user. A user profile typically contains preferences, interests, characteristics, and interaction behavior. However, in its multimodal interaction with a smart environment the user displays characteristics that show how the user, not necessarily consciously, verbally and nonverbally provides the smart environment with useful input and feedback. Especially in ambient intelligence environments we encounter situations where the environment supports interaction between the environment, smart objects (e.g., mobile robots, smart furniture) and human participants in the environment. Therefore it is useful for the profile to contain a physical representation of the user obtained by multi-modal capturing techniques. We discuss the modeling and simulation of interacting participants in a virtual meeting room, we discuss how remote meeting participants can take part in meeting activities and they have some observations on translating research results to smart home environments.     

Finger contour profile based hand biometric recognition

Multimedia Tools and Applications - This paper presents a contactless hand biometric system at unrestricted hand pose environment. A new preprocessing technique is proposed for defining the finger...     

The value of handhelds in smart environments

The severe resource restrictions of computer-augmented everyday artifacts imply substantial problems for the design of applications in smart environments. Some of these problems can be overcome by exploiting the resources, I/O interfaces, and computing capabilities of nearby mobile devices in an ad-hoc fashion. We identify the means by which smart objects can make use of handheld devices such as PDAs and mobile phones, and derive the following major roles of handhelds in smart environments: (1) mobile infrastructure access point; (2) user interface; (3) remote sensor; (4) mobile storage medium; (5) remote resource provider; and (6) weak user identifier. We present concrete applications that illustrate these roles, and describe how handhelds can serve as mobile mediators between computer-augmented everyday artifacts, their users, and background infrastructure services. The presented applications include a remote interaction scenario, a smart medicine cabinet, and an inventory monitoring application.     

Monitoring user activities in smart home environments

Wireless sensor networks (WSNs) enable smart environments to create pervasive and ubiquitous applications, which give context-aware and scalable services to the end users. In this paper, we propose an architecture and design of a web application for a sensor network monitoring. Further, the variation in received signal strength indicator values is used for knowledge extraction. Experiments are conducted in an in-door room environment to determine the activities of a person. For instance, a WSN consisting of Moteiv’s Tmote Sky sensors is deployed in a bedroom to determine the sleeping behavior and other activities of a person.     

Meetings and meeting modeling in smart environments

In this paper we survey our research on smart meeting rooms and its relevance for augmented reality meeting support and virtual reality generation of meetings in real time or off-line. The research reported here forms part of the European 5th and 6th framework programme projects multi-modal meeting manager (M4) and augmented multi-party interaction (AMI). Both projects aim at building a smart meeting environment that is able to collect multimodal captures of the activities and discussions in a meeting room, with the aim to use this information as input to tools that allow real-time support, browsing, retrieval and summarization of meetings. Our aim is to research (semantic) representations of what takes place during meetings in order to allow generation, e.g. in virtual reality, of meeting activities (discussions, presentations, voting, etc.). Being able to do so also allows us to look at tools that provide support during a meeting and at tools that allow those not able to be physically present during a meeting to take part in a virtual way. This may lead to situations where the differences between real meeting participants, human-controlled virtual participants and (semi-) autonomous virtual participants disappear.

Query based visual analysis: spatio-temporal reasoning in computer vision

Two experimental systems for query-based visual analysis are described. The first simulates an image sequence of moving, dividing cells with simple rules and monitors significant visual events. The second processes single raw images of real cells. Both invoke appropriate processing using explicit knowledge to respond to user queries. It is proposed that this selectivity is an essential feature for any system to analyse raw image sequences of moving, dividing cells as the computational expense of allowing all possible processing to proceed is enormous. Processing as required by the query allows adaptive strategies (e.g. different resolutions and focal processing) to be utilized and gives an effective attentional control structure to the system.     

Multimodal identification and tracking in smart environments

We present a model for unconstrained and unobtrusive identification and tracking of people in smart environments and answering queries about their whereabouts. Our model supports biometric recognition based upon multiple modalities such as face, gait, and voice in a uniform manner. The key technical idea underlying our approach is to abstract a smart environment by a state transition system in which each state records a set of individuals who are present in various zones of the environment. Since biometric recognition is inexact, state information is inherently probabilistic in nature. An event abstracts a biometric recognition step, and the transition function abstracts the reasoning necessary to effect state transitions. In this manner, we are able to integrate different biometric modalities uniformly and also different criteria for state transitions. Fusion of biometric modalities is also supported by our model. We define performance metrics for a smart environment in terms of the concepts of ‘precision’ and ‘recall’. We have developed a prototype implementation of our proposed concepts and provide experimental results in this paper. Our conclusion is that the state transition model is an effective abstraction of a smart environment and serves as a good basis for developing practical systems.     

A location model for smart environments

This paper presents a location model for location-aware and user-aware services in smart environments. It can be dynamically organized like a tree based on geographical containment, such as that in a user–room–floor–building hierarchy and each node in the tree can be constructed as an executable software component. The model is unique in existing approaches because it enables location-aware services to be managed without any database servers, it can be managed by multiple computers, and it can provide a unified view of the locations of not only physical entities and spaces, including users and objects, but also computing devices and services. A prototype implementation of this approach was constructed on a Java-based mobile agent system. This paper presents the rationale, design, implementation, and applications of the prototype system.     

普适计算环境下上下文信息推理的研究

从各种低层上下文信息得到对人们更加有用的高层上下文信息即上下文推理是当前研究的热点.针对该问题,采用描述逻辑,研究基于本体模型的上下文推理方法.首先简要介绍基于本体的上下文模型,该模型增加了对上下文特性的建模,然后分别研究基于本体的推理、基于规则的推理及不一致性验证3种推理方式,借助Jena框架的推理接口实现,推理功能全面,通用性强,基本满足了普适计算系统中上下文推理的需求,最后给出了推理的可用性.     

Evidential reasoning for object recognition

The authors present a framework to guide development of evidential reasoning in object recognition systems. Principles of evidential reasoning processes for open-world object recognition are proposed and applied to build evidential reasoning capabilities. The principles summarize research and findings by the authors up through the mid-1990s, including seminal results in object-centered computer vision, figure-ground discrimination, and the application of hierarchical Bayesian inference, Bayesian networks, and decision graphs to evidential reasoning for object recognition.     

Effective opportunistic dissemination of spatio-temporal contents in mobile environments

Dissemination of spatio-temporally valid content from content providers to consumers is critical in certain application contexts as data items could lose their validity across time and space. Content sharing in challenged opportunistic environments remains a research challenge as existing solutions fail to exploit dissemination patterns across spatio-temporal limits. In this paper, we propose spatio-temporal reachability graphs to depict reachability of time- and space-sensitive content in opportunistic mobile environments. Furthermore, we develop an analytical framework to estimate content distribution in such environments and validate its feasibility over long-term datasets. We perform extensive trace-driven simulation studies to determine content dissemination properties of environments with known mobility patterns. The analytical framework estimates dissemination ratio, optimizes parameter setting, and tests transmission capacities of opportunistic environments. Proposed scheme is useful to content providers as well as receivers.