FP7Индивидуална стипендия2012–2014

MACAS · Multi-Modal and Cognition-Aware Systems

7РП — „Хора“ (Действия „Мария Кюри“)

Период
2012-04-01 → 2014-03-31
Финансиране от ЕС
200 372 €
Участници
1
Схема
MC-IEF

Линиите свързват координатора с партньорите.

Накратко на български

Движенията на очите се анализират, за да се разберат когнитивни процеси, като например кога човек припомня нещо от паметта си. Това помага за създаването на компютърни системи, които се адаптират по-добре към нуждите на потребителя.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Multi-Modal and Cognition-Aware Systems

Our eyes are involved in nearly everything that we do in our daily lives. In addition to physical activity, eye movements are also strongly linked to several processes of visual cognition and attention. This suggests that eye movements carry additional information on a user’s context that are difficult – if not impossible – to infer using common modalities, such as body movements or physiological measurements. The first objective of the MACAS project was to develop new knowledge and technology for automatic analysis and recognition of cognitive processes from human visual behaviour – a challenge at the core of ambient intelligence toward systems and services that are proactive and adaptive to human needs. A second objective was to push the state-of-the-art in using gaze for natural and efficient, i.e. calibration-free, human-computer interaction. MACAS finished early due to the fellow taking up a new research position abroad. Nevertheless, the project made a number of contributions torwards the above research objectives. Core contributions of the project during the reporting period include, based on earlier work of the fellow, further investigations on automatic inference of visual memory recall from visual behaviour, a (so far unpublished) study on inferring user expertise as well as another study on inferring document types from visual behaviour, a robust method for smooth pursuit detection as well as for using smooth pursuit movements for interaction and eye tracker calibration, a novel wearable EOG head cap particularly geared for long-term eye movement recordings, as well as two prototype computer vision systems for eye gesture recognition and model-based gaze estimation on unmodified handheld devices. Through close collaborations with researchers in the UK, Switzerland, Germany and Japan, MACAS further contributed to closely related research efforts on calibration-free gaze-based interaction with situated displays and gaze-based object transfer between ambient and hand-held devices, as well as physical behaviour modelling and qualitative activity recognition. Finally, through the MACAS project, we organised two workshops on pervasive eye tracking and mobile eye-based human-computer interaction at the leading conferences in ubiquitous computing (UbiComp) and eye movement research (ECEM).

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

This research proposal is embedded in the research fields of ambient intelligence and human-computer interaction. One goal of both fields is to develop computing systems that are able to continuously monitor, learn from and proactively adapt to the state (or context) of the user. The proposal aims to add an exciting new concept to this topic - the use of eye movements to infer the cognitive user context. This project has the potential to lead to the development of cognition-aware systems, thus opening the door to a new area of research on the boundary between the cognitive and computer sciences.This highly inter-disciplinary project will focus on simultaneous assessment of eye and body movements as particularly promising means to infer the cognitive context of the user. The two main objectives are 1) the development of a machine learning framework for real-time inference of selected aspects of visual cognition from eye movements and 2) the extension of this framework to using additional sensing modalities, particularly body movements and physiological parameters.These objectives will be achieved by running a series of empirical studies, by developing pattern recognition and machine learning techniques specifically geared for simultaneous classification of eye and body movements, and by evaluating these techniques in real-time in a driving simulator. Experimental data will be collected using a wearable eye tracker and body-worn motion and physiological sensors.The current proposal directly contributes to Challenge 1 of the FP7 Work Program (Objective ICT-2011.1.3) and Challenge 2 (Cognitive Systems and Robotics). Its outcomes are expected to contribute to our understanding of natural cognitive systems, specifically cognitive processes in natural visual behaviour, attention and eye-hand coordination, as well as to contribute new computational methods for analysis, modeling and machine recognition of visual cognitive processes from time series eye movement data.""

Оригинален текст от CORDIS (на английски).

Участници

Връзки

Данни: CORDIS, © Европейски съюз