19,439 research outputs found
Affordances and Safe Design of Assistance Wearable Virtual Environment of Gesture
Safety and reliability are the main issues for designing assistance wearable
virtual environment of technical gesture in aerospace, or health application
domains. That needs the integration in the same isomorphic engineering
framework of human requirements, systems requirements and the rationale of
their relation to the natural and artifactual environment.To explore coupling
integration and design functional organization of support technical gesture
systems, firstly ecological psychologyprovides usa heuristicconcept: the
affordance. On the other hand mathematical theory of integrative physiology
provides us scientific concepts: the stabilizing auto-association principle and
functional interaction.After demonstrating the epistemological consistence of
these concepts, we define an isomorphic framework to describe and model human
systems integration dedicated to human in-the-loop system engineering.We
present an experimental approach of safe design of assistance wearable virtual
environment of gesture based in laboratory and parabolic flights. On the
results, we discuss the relevance of our conceptual approach and the
applications to future assistance of gesture wearable systems engineering
Building a sign language corpus for use in machine translation
In recent years data-driven methods of machine translation (MT) have overtaken rule-based approaches as the predominant means of automatically translating between languages. A pre-requisite for such an approach is a parallel corpus of the source and target languages. Technological developments in sign language (SL) capturing, analysis and processing tools now mean that SL corpora are
becoming increasingly available. With transcription and language analysis tools being mainly designed and used for linguistic purposes, we describe the process of creating a multimedia parallel corpus specifically for the purposes of English to Irish Sign Language (ISL) MT. As part of our larger project on localisation, our research is focussed on developing assistive technology for patients with limited English in the domain of healthcare. Focussing on the first point of contact a patient has with a GP’s office, the
medical secretary, we sought to develop a corpus from the dialogue between the two parties when scheduling an appointment. Throughout the development process we have created one parallel corpus in six different modalities from this initial dialogue. In this paper we discuss the multi-stage process of the development of this parallel corpus as individual and interdependent entities, both for
our own MT purposes and their usefulness in the wider MT and SL research domains
Adaptive modality selection algorithm in robot-assisted cognitive training
© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Interaction of socially assistive robots with users is based on social cues coming from different interaction modalities, such as speech or gestures. However, using all modalities at all times may be inefficient as it can overload the user with redundant information and increase the task completion time. Additionally, users may favor certain modalities over the other as a result of their disability or personal preference. In this paper, we propose an Adaptive Modality Selection (AMS) algorithm that chooses modalities depending on the state of the user and the environment, as well as user preferences. The variables that describe the environment and the user state are defined as resources, and we posit that modalities are successful if certain resources possess specific values during their use. Besides the resources, the proposed algorithm takes into account user preferences which it learns while interacting with users. We tested our algorithm in simulations, and we implemented it on a robotic system that provides cognitive training, specifically Sequential memory exercises. Experimental results show that it is possible to use only a subset of available modalities without compromising the interaction. Moreover, we see a trend for users to perform better when interacting with a system with implemented AMS algorithm.Peer ReviewedPostprint (author's final draft
The Evolution of First Person Vision Methods: A Survey
The emergence of new wearable technologies such as action cameras and
smart-glasses has increased the interest of computer vision scientists in the
First Person perspective. Nowadays, this field is attracting attention and
investments of companies aiming to develop commercial devices with First Person
Vision recording capabilities. Due to this interest, an increasing demand of
methods to process these videos, possibly in real-time, is expected. Current
approaches present a particular combinations of different image features and
quantitative methods to accomplish specific objectives like object detection,
activity recognition, user machine interaction and so on. This paper summarizes
the evolution of the state of the art in First Person Vision video analysis
between 1997 and 2014, highlighting, among others, most commonly used features,
methods, challenges and opportunities within the field.Comment: First Person Vision, Egocentric Vision, Wearable Devices, Smart
Glasses, Computer Vision, Video Analytics, Human-machine Interactio
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