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.

In contrast with design flaws that occur in user interfaces, design flaws in physical spaces have a much higher cost and impact. Software is in fact fairly easy to change and update in contrast with legacy physical constructions where updating their physical appearance is often not an option. We present the Feedforward Torch, a mobile projection system that targets the augmentation of legacy hardware with feedforward information. Feedforward explains users what the results of their action will be, and can thus be seen as the opposite of feedback. A first user study suggests that providing feedforward in these environments could improve their usability.

Activity-Based Computing (ABC) has been proposed as an organisational structure for local desktop management and knowledge work. Knowledge work, however, typically occurs in partially overlapping subgroups and involves the use of multiple devices. We introduce co-Activity Manager, an ABC approach that (i) supports activity sharing for multiple collaborative contexts, (ii) includes collaborative tools into the activity abstraction and (iii) supports multiple devices by seamlessly integrated cloud support for documents and activity storage. Our 14 day field deployment in a multidisciplinary software development team showed that activity sharing is used as a starting point for long-term collaboration while integrated communication tools and cloud support are used extensively during the collaborative activities. The study also showed that activities are used in different ways ranging from project descriptions to to-do lists, thereby confirming that a document-driven activity roaming model seems to be a good match for collaborative knowledge work.

Interactive surfaces have great potential for co-located collaboration because of their ability to track multiple inputs simultaneously. However, the multi-user experience on these devices could be enriched significantly if touch points could be associated with a particular user. Existing approaches to user identification are intrusive, require users to stay in a fixed position, or suffer from poor accuracy. We present a non-intrusive, high-accuracy technique for mapping touches to their corresponding user in a collaborative environment. By mounting a high-resolution camera above the interactive surface, we are able to identify touches reliably without any extra instrumentation, and users are able to move around the surface at will. Our technique, which leverages the back of users' hands as identifiers, supports walk-up-and-use situations in which multiple people interact on a shared surface.