Accessibility-based reranking in multimedia search engines

Multimedia Tools and Applications - Traditional multimedia search engines retrieve results based mostly on the query submitted by the user, or using a log of previous searches to provide...     

Multi-view human movement recognition based on fuzzy distances and linear discriminant analysis

In this paper, a novel multi-view human movement recognition method is presented. A novel representation of multi-view human movement videos is proposed that is based on learning basic multi-view human movement primitives, called multi-view dynemes. The movement video is represented in a new feature space (called dyneme space) using these multi-view dynemes, thus producing a time invariant multi-view movement representation. Fuzzy distances from the multi-view dynemes are used to represent the human body postures in the dyneme space. Three variants of Linear Discriminant Analysis (LDA) are evaluated to achieve a discriminant movement representation in a low dimensionality space. The view identification problem is solved either by using a circular block shift procedure followed by the evaluation of the minimum Euclidean distance from any dyneme, or by exploiting the circular shift invariance property of the Discrete Fourier Transform (DFT). The discriminant movement representation combined with camera viewpoint identification and a nearest centroid classification step leads to a high human movement classification accuracy.     

Enabling user interface developers to experience accessibility limitations through visual,hearing, physical and cognitive impairment simulation

His paper presents a tool facilitating developers of user interfaces (UIs) to experience accessibility limitations that can be posed from various disabilities during the interaction of impaired users with their developments. In this respect, various aspects of visual, hearing, physical and cognitive impairments have been modelled through filters providing approximate, yet, realistic simulations over them. These filters have formed the basis for the developed tool, which can be used either on its own (as a standalone application), or be embedded in the NetBeans Integrated Development Environment. The tool, named DIAS, allows for impairment simulations to be performed over Java, mobile and web applications. Moreover, it integrates two of the most common assistive technologies (ATs), namely a screen reader and a magnifier. As a result, developers of UIs can not only experience how interaction would be affected from various impairments, but they can also understand how their developments would be perceived by impaired users through an AT. This work aims to provide an integrated, practical solution for impairment simulation, which could be easily adopted by developers, thus realistically increasing the possibilities for the future development of interactive applications that are more accessible to users with disabilities.     

Autonomous stair-climbing with miniature jumping robots.

The problem of vision-guided control of miniature mobile robots is investigated. Untethered mobile robots with small physical dimensions of around 10 cm or less do not permit powerful onboard computers because of size and power constraints. These challenges have, in the past, reduced the functionality of such devices to that of a complex remote control vehicle with fancy sensors. With the help of a computationally more powerful entity such as a larger companion robot, the control loop can be closed. Using the miniature robot's video transmission or that of an observer to localize it in the world, control commands can be computed and relayed to the inept robot. The result is a system that exhibits autonomous capabilities. The framework presented here solves the problem of climbing stairs with the miniature Scout robot. The robot's unique locomotion mode, the jump, is employed to hop one step at a time. Methods for externally tracking the Scout are developed. A large number of real-world experiments are conducted and the results discussed.     

Hand dexterity assessment based on mouse pointer trajectory measurements in children with learning disabilities

Universal Access in the Information Society - We present an investigation of the systematic differences in upper limb motor skills between children with learning disabilities (LDs) and children...     

A knowledge-based approach to user interface adaptation from preferences and for special needs

Moving between devices is omnipresent, but not for people with disabilities or those who require specific accessibility options. Setting up assistive technologies or finding settings to overcome a certain barrier can be a demanding task for people without technical skills. Context-sensitive adaptive user interfaces are advancing, although migrating access features from one device to another is very rarely addressed. In this paper, we describe the knowledge-based component of the Global Public Inclusive Infrastructure that infers how a device shall be best configured at the operating system layer, the application layer and the web layer to meet the requirements of a user including possible special needs or disabilities. In this regard, a mechanism to detect and resolve conflicting accessibility policies as well as recommending preference substitutes is a main requirement, as elaborated in this paper. As the proposed system emulates decision-making of accessibility experts, we validated the automatic deduced configurations against manual configurations of ten accessibility experts. The assessment result shows that the average matching score of the developed system is high. Thus, the proposed system can be considered capable of making precise decisions towards personalizing user interfaces based on user needs and preferences.     

The impact of computer self-efficacy,situational interest and academic self-concept in virtual communities of inquiry during the distance learning procedures through Second Life

The current study investigates a case where the online learning procedure in three-dimensional (3D) technologically-advanced environments of the Web 2.0 is growing at an exponential rate. In this occasion it is highly imperative need to understand students’ interactions in this innovative mode of e-Education that requires from educators and scholars not only analysis conceptually, but also an empirically-driven optimization. The community of inquiry (CoI) model (or framework) consists to be as one of the most prominent multi-dimensional constructs that it is widely used to represent several distinct dimensions of social presence, teaching presence and cognitive presence, as a unique and fundamental theoretical concept to measure students’ interactions in contemporary electronic environments. Although, the effectiveness of these multi-dimensional constructs creates a dilemma to researchers who want the breadth and comprehensiveness of this model for the precision and clarity of users’ (instructors and students) dimensions with other motivational and learning variables. To address this dilemma, the current empirical study presents statistical analyses from the “trinity” constructs of the CoI model by utilizing correlation and hierarchical regression analyses with two fundamental motivational (computer self-efficacy and situational interest) and another one learning (academic self-concept) variables. This study goes one step further and introduces the conspicuously indisputable intervention of a virtual (V)CoI and its utilization in multi-user virtual worlds, like Second Life (SL). The study findings of one hundred thirty-five (135) participants who enrolled in several online sessions unveiled that the situational interest was the only significant predictor of social presence. The computer self-efficacy was not a significant predictor of the CoI model, while on the other hand academic self-concept was a significant predictor in a revamped attempt to validate the strong relationship among constructs within it. According to the aforementioned reasons, it can be surmised that the successful combination of the VCoI in Second Life, surpassing irrefutable and inherent shortcomings to a future-driven sustainable use and growth.     

A New Methodology for Efficient Classification of Multispectral Satellite Images Using Neural Network Techniques

A methodology based on self-organizing feature maps and indexing techniques for time and memory efficient neural network training and classification of large volumes of remotely sensed data is presented. Results on land-cover classification of multispectral satellite images using two popular neural models show orders of magnitude of speedup with respect to both training and classification times. The generality of the proposed methodology is demonstrated with a dramatic improvement of the classification time of the k-nearest neighbors statistical classifier.