Intelligent User Interfaces can benefit from having knowledge on the user's emotion. However, current implementations to detect affective states, are often constraining the user's freedom of movement by instrumenting her with sensors. This prevents affective computing from being deployed in naturalistic and ubiquitous computing contexts. In this paper, we present a novel system called mASqUE, which uses a set of association rules to infer someone's affective state from their body postures. This is done without any user instrumentation and using off-the-shelf and non-expensive commodity hardware: a depth camera tracks the body posture of the users and their postures are also used as an indicator of their openness. By combining the posture information with physiological sensors measurements we were able to mine a set of association rules relating postures to affective states. We demonstrate the possibility of inferring affective states from body postures in ubiquitous computing environments and our study also provides insights how this opens up new possibilities for IUI to access the affective states of users from body postures in a nonintrusive way.

Professional video searchers typically have to search for partic- ular video fragments in a vast video archive that contains many hours of video data. Without having the right video archive exploration tools, this is a difficult and time consuming task that induces hours of video skimming. We propose the video archive explorer, a video exploration tool that provides visual representations of automatically detected concepts to facilitate individual and collaborative video search tasks. This video archive explorer is developed by employing a user-centred methodology, which ensures that the tool is more likely to fit to the end user needs. A qualitative evaluation with professional video searchers shows that the combination of automatic video indexing, interactive visualisations and user-centred design can result in an increased usability, user satisfaction and productivity.

The television remains a central hub in the home environment. We believe that in order to maintain its central role future TV's will need to incorporate empathic features. These will be delivered by interacting with other personal devices in home and services in the cloud. This position paper illustrates the common as well as the individual views of several Belgian partners working around a common scenario in the ITEA2 'Empathic Products' project.

Feedback and affordances are two of the most well-known principles in interaction design. Unfortunately, the related and equally important notion of feedforward has not been given as much consideration. Nevertheless, feedforward is a powerful design principle for bridging Norman's Gulf of Execution. We reframe feedforward by disambiguating it from related design principles such as feedback and perceived affordances, and identify new classes of feedforward. In addition, we present a reference framework that provides a means for designers to explore and recognize different opportunities for feedforward.

In todays videogames user feedback is often provided through raw statistics and scoreboards. We envision that incorporating empathic feedback matching the player's current mood will improve the overall gaming experience. In this paper we present Bro-cam, a novel system that provides empathic feedback to the player based on their body postures. Different body postures of the players are used as an indicator for their openness. From their level of openness, Bro-cam profiles the players into different personality types ranging from introvert to extrovert. Empathic feedback is then automatically generated and matched to their preferences for certain humoristic feedback statements. We use a depth camera to track the player's body postures and movements during the game and analyze these to provide customized feedback. We conducted a user study involving 32 players to investigate their subjective assessment on the empathic game feedback. Semi-structured interviews reveal that participants were positive about the empathic feedback and Bro-cam significantly improves their game experience.

Modern knowledge work consists of both individual and highly collaborative activities that are typically composed of a number of configuration, coordination and articulation processes. The desktop interface today, however, provides very little support for these processes and rather forces knowledge workers to adapt to the technology. We introduce co-Activity Manager, an activity-centric desktop system that (i) provides tools for ad hoc dynamic configuration of a desk- top working context, (ii) supports both explicit and implicit articulation of ongoing work through a built-in collaboration manager and (iii) provides the means to coordinate and share working context with other users and devices. In this paper, we discuss the activity theory informed design of co-Activity Manager and report on a 14 day field deployment in a multi-disciplinary software development team. The study showed that the activity-centric workspace supports different individ- ual and collaborative work configuration practices and that activity-centric collaboration is a two-phase process consisting of an activity sharing and per-activity coordination phase.