EYE AND GAZE TRACKING ALGORITHM FOR COLLABORATIVE LEARNING SYSTEM

International audienceOur work focuses on the interdisciplinary field of detailed analysis of behaviors exhibited by individuals during sessions of distributed collaboration. With a particular focus on ergonomics, we propose new mechanisms to be integrated into existing tools to enable increased productivity in distributed learning and working. Our technique is to record ocular movements (eye tracking) to analyze various scenarios of distributed collaboration in the context of computer-based training. In this article, we present a low-cost oculometric device that is capable of making ocular measurements without interfering with the natural behavior of the subject. We expect that this device could be employed anywhere that a natural, non-intrusive method of observation is required, and its low-cost permits it to be readily integrated into existing popular tools, particularly E-learning campus

Augmented reality interaction and vision-based tracking

Master'sMASTER OF ENGINEERIN

A comparative study of the sense of presence and anxiety in an invisible marker versus a marker Augmented Reality system for the treatment of phobia towards small animals

Phobia towards small animals has been treated using exposure in vivo and virtual reality. Recently, augmented reality (AR) has also been presented as a suitable tool. The first AR system developed for this purpose used visible markers for tracking. In this first system, the presence of visible markers warns the user of the appearance of animals. To avoid this warning, this paper presents a second version in which the markers are invisible. First, the technical characteristics of a prototype are described. Second, a comparative study of the sense of presence and anxiety in a non-phobic population using the visible marker-tracking system and the invisible marker-tracking system is presented. Twenty-four participants used the two systems. The participants were asked to rate their anxiety level (from 0 to 10) at 8 different moments. Immediately after their experience, the participants were given the SUS questionnaire to assess their subjective sense of presence. The results indicate that the invisible marker-tracking system induces a similar or higher sense of presence than the visible marker-tracking system, and it also provokes a similar or higher level of anxiety in important steps for therapy. Moreover, 83.33% of the participants reported that they did not have the same sensations/surprise using the two systems, and they scored the advantage of using the invisible marker-tracking system (IMARS) at 5.19 +/- 2.25 (on a scale from 1 to 10). However, if only the group with higher fear levels is considered, 100% of the participants reported that they did not have the same sensations/surprise with the two systems, scoring the advantage of using IMARS at 6.38 +/- 1.60 (on a scale from 1 to 10). (C) 2011 Elsevier Ltd. All rights reserved.Juan, M.; Joele, D. (2011). A comparative study of the sense of presence and anxiety in an invisible marker versus a marker Augmented Reality system for the treatment of phobia towards small animals. International Journal of Human-Computer Studies. 69(6):440-453. doi:10.1016/j.ijhcs.2011.03.00244045369

Keyframe Tagging: Unambiguous Content Delivery for Augmented Reality Environments

Context: When considering the use of Augmented Reality to provide navigation cues in a completely unknown environment, the content must be delivered into the environment with a repeatable level of accuracy such that the navigation cues can be understood and interpreted correctly by the user. Aims: This thesis aims to investigate whether a still image based reconstruction of an Augmented Reality environment can be used to develop a content delivery system that providers a repeatable level of accuracy for content placement. It will also investigate whether manipulation of the properties of a Spatial Marker object is sufficient to reduce object selection ambiguity in an Augmented Reality environment. Methods: A series of experiments were conducted to test the separate aspects of these aims. Participants were required to use the developed Keyframe Tagging tool to introduce virtual navigation markers into an Augmented Reality environment, and also to identify objects within an Augmented Reality environment that was signposted using different Virtual Spatial Markers. This tested the accuracy and repeatability of content placement of the approach, while also testing participants’ ability to reliably interpret virtual signposts within an Augmented Reality environment. Finally the Keyframe Tagging tool was tested by an expert user against a pre-existing solution to evaluate the time savings offered by this approach against the overall accuracy of content placement. Results: The average accuracy score for content placement across 20 participants was 64%, categorised as “Good” when compared with an expert benchmark result, while no tags were considered “incorrect” and only 8 from 200 tags were considered to have “Poor” accuracy, supporting the Keyframe Tagging approach. In terms of object identification from virtual cues, some of the predicted cognitive links between virtual marker property and target object did not surface, though participants reliably identified the correct objects across several trials. Conclusions: This thesis has demonstrated that accurate content delivery can be achieved through the use of a still image based reconstruction of an Augmented Reality environment. By using the Keyframe Tagging approach, content can be placed quickly and with a sufficient level of accuracy to demonstrate its utility in the scenarios outlined within this thesis. There are some observable limitations to the approach, which are discussed with the proposals for further work in this area

Contribuciones a la estimación de la pose de la cámara en aplicaciones industriales de realidad aumentada

Augmented Reality (AR) aims to complement the visual perception of the user environment superimposing virtual elements. The main challenge of this technology is to combine the virtual and real world in a precise and natural way. To carry out this goal, estimating the user position and orientation in both worlds at all times is a crucial task. Currently, there are numerous techniques and algorithms developed for camera pose estimation. However, the use of synthetic square markers has become the fastest, most robust and simplest solution in these cases. In this scope, a big number of marker detection systems have been developed. Nevertheless, most of them presents some limitations, (1) their unattractive and non-customizable visual appearance prevent their use in industrial products and (2) the detection rate is drastically reduced in presence of noise, blurring and occlusions. In this doctoral dissertation the above-mentioned limitations are addressed. In first place, a comparison has been made between the different marker detection systems currently available in the literature, emphasizing the limitations of each. Secondly, a novel approach to design, detect and track customized markers capable of easily adapting to the visual limitations of commercial products has been developed. In third place, a method that combines the detection of black and white square markers with keypoints and contours has been implemented to estimate the camera position in AR applications. The main motivation of this work is to offer a versatile alternative (based on contours and keypoints) in cases where, due to noise, blurring or occlusions, it is not possible to identify markers in the images. Finally, a method for reconstruction and semantic segmentation of 3D objects using square markers in photogrammetry processes has been presented.La Realidad Aumentada (AR) tiene como objetivo complementar la percepción visual del entorno circunstante al usuario mediante la superposición de elementos virtuales. El principal reto de dicha tecnología se basa en fusionar, de forma precisa y natural, el mundo virtual con el mundo real. Para llevar a cabo dicha tarea, es de vital importancia conocer en todo momento tanto la posición, así como la orientación del usuario en ambos mundos. Actualmente, existen un gran número de técnicas de estimación de pose. No obstante, el uso de marcadores sintéticos cuadrados se ha convertido en la solución más rápida, robusta y sencilla utilizada en estos casos. En este ámbito de estudio, existen un gran número de sistemas de detección de marcadores ampliamente extendidos. Sin embargo, su uso presenta ciertas limitaciones, (1) su aspecto visual, poco atractivo y nada customizable impiden su uso en ciertos productos industriales en donde la personalización comercial es un aspecto crucial y (2) la tasa de detección se ve duramente decrementada ante la presencia de ruido, desenfoques y oclusiones Esta tesis doctoral se ocupa de las limitaciones anteriormente mencionadas. En primer lugar, se ha realizado una comparativa entre los diferentes sistemas de detección de marcadores actualmente en uso, enfatizando las limitaciones de cada uno. En segundo lugar, se ha desarrollado un novedoso enfoque para diseñar, detectar y trackear marcadores personalizados capaces de adaptarse fácilmente a las limitaciones visuales de productos comerciales. En tercer lugar, se ha implementado un método que combina la detección de marcadores cuadrados blancos y negros con keypoints y contornos, para estimar de la posición de la cámara en aplicaciones AR. La principal motivación de este trabajo se basa en ofrecer una alternativa versátil (basada en contornos y keypoints) en aquellos casos donde, por motivos de ruido, desenfoques u oclusiones no sea posible identificar marcadores en las imágenes. Por último, se ha desarrollado un método de reconstrucción y segmentación semántica de objetos 3D utilizando marcadores cuadrados en procesos de fotogrametría