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The purpose of this study is to present a depth information-based solution for automatic camera control, depending on the presenter’s moving positions. Talks, presentations and lectures are often captured on video to give a broad audience the possibility to (re-)access the content. As presenters are often moving around during a talk, it is necessary to steer recording cameras.

We use depth information from Kinect to implement a prototypical application to automatically steer multiple cameras for recording a talk.

We present our experiences with the system during actual lectures at a university. We found out that Kinect is applicable for tracking a presenter during a talk robustly. Nevertheless, our prototypical solution reveals potential for improvements, which we discuss in our future work section.

Tracking a presenter is based on a skeleton model extracted from depth information instead of using two-dimensional (2D) motion- or brightness-based image processing techniques. The solution uses a scalable networking architecture based on publish/subscribe messaging for controlling multiple video cameras.

This paper aims to elucidate perceptions of safe driving and social norms in relation to driving motorbikes in the Vietnamese context.

A series of focus groups was undertaken in relation to driving practices from a number of groups: adolescents, families and adult males and females. The discussion centred on how driving behaviours were socialised within the various groups.

The research highlighted some very interesting social dynamics in relation to how safe driving habits are established and supported within the social context. In particular, the separation of descriptive and injunctive norms and the role such norms play in socialising driving behaviours, safe or otherwise.

The implications for social marketing practice are considerable, especially in the Vietnamese context where injunctive norms are difficult to portray, given the dynamics of the media landscape. Social marketing campaigns will need to have a broader consideration of how to establish descriptive norms, bearing in mind the social milieu in which the behaviours occur.

This research is the first of its kind in the Vietnamese context. While much practice-led innovation is occurring in the region, there is little extant research on the topic of social norms and the socialisation of behaviours within the Southeast Asian region.

AAL (Ambient Assisted Living) is lacking a RM (Reference Model) to serve as an abstraction of the domain. Therefore, to help implement new architectures established on the prior experiences of the designer’s expertise and former competences, in this paper, we propose a novel approach of an AAL RM. Our objective is to handle the resolution of conflicts that appear between the developers, and give an overview of the basis for implementing concrete software architectures for different families of AAL applications. Our proposed RM is a standardized clarification for developers to apply in the process of the design and implementation. We illuminate the AAL domain fundamental dimensions and we established a formal RM with an infrastructure that could survive the domain’s progression. To achieve integrated system-of-systems composed of systems, subsystems and components, our RM describes a standard and regulated structure to be established. High-level elements, essential properties and characteristics that must appear in the application’s design are described and illustrated in this work.

Senior citizen falls are one of the highest-cost factors of healthcare within this population group. Various approaches for automatic fall detection exist. However, little is known about the seniors’ acceptance of these systems. The purpose of this paper is to investigate the acceptance of automatic fall detection devices as well as the technological commitment and the health status in community-dwelling adults with a predefined risk of falling.

Seniors with a risk of falling were equipped with either an accelerometer or an accelerometer with an additional visual and optical fall detection system in a sub-group of the study population for a period of eight weeks. Pre- and post-study questionnaires were used to assess attitudes and acceptance toward technology.

In total, 14 subjects with a mean age of 75.1 years completed the study. Acceptance toward all sensors was high and subjects were confident in their ability to handle technology. Medical assessments showed only very mild physical and no mental impairments. Measures that assured subjects privacy protection were welcomed. Sensor technology should be as unobtrusive as possible.

Privacy protection and uncomplicated use of the fall detection equipment led to high acceptance in seniors with high-technical commitment and good health status. Issues to further improve acceptance could be identified. Future research on different populations is necessary.