Publications - BullsEye

Quadropong - Conditions for Mediating Collaborative Interaction in a Co-located Collaborative Digital Game using Multi-Display Composition

Eriksson, E., Petersen, J. O., Bagge, R., et al. — Sat, 01 Oct 2022 16:02:04 +0200

In this demo, we present Quadropong, a co-located collaborative digital game using multi-display composition. It consists of conditions in the form of ten game instances designed to mediate various levels of collaborative interaction in players. The conditions were designed based on variations in interdependence and in symmetry and asymmetry in skills and resources.
The preliminary results from playtests indicate that it is possible to design conditions to mediate various levels of collaborative interaction.

Consent-O-Matic

Nouwens, M., Bagge, R., Kristensen, J. B., Klokmose, C. N. — Fri, 01 Apr 2022 16:02:04 +0200

The majority of consent pop-ups on the web do not meet the requirements for legally valid consent laid out in the General Data Protection Regulation (GDPR). In the face of a lack of enforcement, we present the browser extension Consent-O-Matic which uses adversarial interoperability to automatically answer these pop-ups based on the user's preferences. We document how the current implementation of these pop-ups support and inhibit interoperability, focussing on the difference between static and dynamic HTML, the quality of the semantic markup, and the visibility of the system's state; and we present the implementation of Consent-O-Matic. Lastly, we discuss the possibilities, limitations, and concerns of an adversarial approach.

Varv

Fri, 01 Apr 2022 16:02:04 +0200

Most modern applications are immutable and turn-key despite the acknowledged benefits of empowering users to modify their software. Writing extensible software remains challenging, even for expert programmers. Reprogramming or extending existing software is often laborious or wholly blocked, requiring sophisticated knowledge of application architecture or setting up a development environment. We present Varv, a programming model representing reprogrammable interactive software as a declarative data structure. Varv defines interactive applications as a set of concepts that consist of a schema and actions. Applications in Varv support incremental modification, allowing users to reprogram through addition and selectively suppress, modify, or add behavior. Users can define high-level concepts, creating an abstraction layer and effectively a domain-specific language for their application domain, emphasizing reuse and modification. We demonstrate the reprogramming and collaboration capabilities of Varv in two case studies and illustrate how the event engine allows for extensive tooling support.

Codestrates V2

Borowski, M., Kristensen, J. B., Bagge, R., Klokmose, C. N. — Fri, 01 Jan 2021 16:02:04 +0100

This report presents the Codestrates v2 development platform for Webstrates. Webstrates is an experimental platform to explore the vision of computational media. Codestrates v2 consists of three components: The Webstrates Package Manager, the Execution engine, and the authoring environment Cauldron. Together, the three components create a powerful development platform for Webstrates on top of Webstrates. This report summarizes the background of the project and its original motivation. We introduce the three components, explain their functionality and use, and provide details about how they are implemented. Finally, two example cases illustrate how the platform allows to create a simple todo list application and a computational notebook.

Videostrates

Tue, 01 Jan 2019 16:02:04 +0100

BullsEye

Klokmose, C. N., Kristensen, J. B., Bagge, R., Halskov, K. — Wed, 01 Jan 2014 16:02:04 +0100

This paper proposes a series of techniques for improving the precision of optical fiducial tracking on tangible tabletops. The motivation is to enable convincing interactive projection mapping on tangibles on the table, which requires a high precision tracking of the location of tangibles. We propose a new fiducial design optimized for GPU based tracking, a technique for calibrating light that allows for computation on a greyscale image rather than a binarized black and white image, an automated technique for compensating for optical distortions in the camera lenses, and a tracking algorithm implemented primarily in shaders on the GPU. The techniques are realized in the BullsEye computer vision software. We demonstrate experimentally that BullsEye provides sub-pixel accuracy down to a tenth of a pixel, which is a significant improvement compared to the commonly used reacTIVision software.