Nowadays, handheld devices are capable of displaying augmented environments in which virtual content overlaps reality. To interact with these environments it is necessary to use a manipulation technique. The objective of a manipulation technique is to define how the input data modify the properties of the virtual objects. Current devices have multi-touch screens that can serve as input. Additionally, the position and rotation of the device can also be used as input creating both an opportunity and a design challenge. In this paper we compared three manipulation techniques which namely employ multi-touch, device position and a combination of both. A user evaluation on a docking task revealed that combining multitouch and device movement yields the best task completion time and efficiency. Nevertheless, using only the device movement and orientation is more intuitive and performs worse only in large rotations.

Digital educational games research tends to lack ecological validity by not adequately taking into account the views and perspectives of children and young people with autism spectrum disorders (ASD). This paper is a pilot study that explores and analyses an academic-based educational game that was co-designed with and for young people with ASD. The serious game aims to help the players learn Geography-specific knowledge and integrates several strategic features so that users can collaborate together against the computer or compete against each other. The educational game was evaluated over 5 sessions by 3 peer teams from 2 different special educational institutions, involving a total of 6 students with ASD. The participants were positive about their enjoyment, motivation, and social engagement. The results showed that the players' level of competitiveness not only influenced the experience within the game but also the interaction within the peer teams. The game mechanisms did help the participants with ASD increase their knowledge in Geography content. The main conclusion is that there are considerable benefits of including children with ASD in the design process and future research should explore more fully on how their involvement can enhance curriculum-based learning as well as social engagement within the classroom.

Manipulation is one of the most important tasks required in virtual environments and thus it has been thoroughly studied for widespread input devices such as mice or multi-touch screens. Nowadays, the Kinect sensor has turned mid-air interaction into another affordable and popular way of interacting. Mid-air interaction enables the possibility of interacting remotely without any physical contact and in a more natural manner. Nonetheless, although some scattered manipulation techniques have been proposed for mid-air interaction, there is a lack of evaluations and comparisons that hinders the selection and development of these techniques. To solve this issue, we gathered four design choices that can be used to classify mid-air manipulation techniques. Namely, choices are based on the required number of hands, separation of translation-rotation, decomposition of rotation, and interaction metaphors. Furthermore, we developed, adapted, and compared three manipulation techniques selected for studying the implications of the design choices. These implications are useful to select among already existing techniques as well as to inform technique developers.

Theory shows that huge amount of labelled data are needed in order to achieve reliable classification/regression methods when using deep/machine learning techniques. However, in the eye tracking field, manual annotation is not a feasible option due to the wide variability to be covered. Hence, techniques devoted to synthesizing images show up as an opportunity to provide vast amounts of annotated data. Considering that the well-known UnityEyes tool provides a framework to generate single eye images and taking into account that both eyes information can contribute to improve gaze estimation accuracy we present U2Eyes dataset, that is publicly available. It comprehends about 6 million of synthetic images containing binocular data. Furthermore, the physiology of the eye model employed is improved, simplified dynamics of binocular vision are incorporated and more detailed 2D and 3D labelled data are provided. Additionally, an example of application of the dataset is shown as work in progress. Employing U2Eyes as training framework Supervised Descent Method (SDM) is used for eyelids segmentation. The model obtained as result of the training process is then applied on real images from GI4E dataset showing promising results.

Abstract. In autism and technology research, technologies are often developed by researchers targeting specific social and communication difficulties experienced by individuals with autism. In some technologybased projects, children and adults with autism as well as parents, carers, teachers, and other professionals, are involved as users, informers, and (more rarely) as co-designers. However, much less is known about the views of the autism community about the needs they identify as areas that could be addressed through innovative technological solutions. This paper describes the ASCmeI.T. project which encourages members of the autism community to download a free app to answer the question: If there was one new technology to help people with autism, what would it be? This project provides a model of e-participation in which people from the autism community are involved from the start so that new developments in digital technologies can be better matched to support the needs of users.