Interactive Diffraction from Biological Nanostructures

We describe a technique for interactive rendering of diffraction effects produced by biological nanostructures such as snake skin surface gratings. Our approach uses imagery from atomic force microscopy that accurately captures the nanostructures responsible for structural coloration, that is, coloration due to wave interference, in a variety of animals. We develop a rendering technique that constructs bidirectional reflection distribution functions (BRDFs) directly from the measured data and leverages precomputation to achieve interactive performance. We demonstrate results of our approach using various shapes of the surface grating nanostructures. Finally, we evaluate the accuracy of our precomputation-based technique and compare to a reference BRDF construction technique.

Interactive free viewpoint video streaming using prioritized network coding

In free viewpoint applications, the images are captured by an array of cameras that acquire a scene of interest from different perspectives. Any intermediate viewpoint not included in the camera array can be virtually synthesized by the decoder, at a quality that depends on the distance between the virtual view and the camera views available at decoder. Hence, it is beneficial for any user to receive camera views that are close to each other for synthesis. This is however not always feasible in bandwidth-limited overlay networks, where every node may ask for different camera views. In this work, we propose an optimized delivery strategy for free viewpoint streaming over overlay networks. We introduce the concept of layered quality-of-experience (QoE), which describes the level of interactivity offered to clients. Based on these levels of QoE, camera views are organized into layered subsets. These subsets are then delivered to clients through a prioritized network coding streaming scheme, which accommodates for the network and clients heterogeneity and effectively exploit the resources of the overlay network. Simulation results show that, in a scenario with limited bandwidth or channel reliability, the proposed method outperforms baseline network coding approaches, where the different levels of QoE are not taken into account in the delivery strategy optimization.

Combining Bottom-up and Top-down Generation of Interactive Knowledge Maps for Enterprise Search

Our research project develops an intranet search engine with concept- browsing functionality, where the user is able to navigate the conceptual level in an interactive, automatically generated knowledge map. This knowledge map visualizes tacit, implicit knowledge, extracted from the intranet, as a network of semantic concepts. Inductive and deductive methods are combined; a text ana- lytics engine extracts knowledge structures from data inductively, and the en- terprise ontology provides a backbone structure to the process deductively. In addition to performing conventional keyword search, the user can browse the semantic network of concepts and associations to find documents and data rec- ords. Also, the user can expand and edit the knowledge network directly. As a vision, we propose a knowledge-management system that provides concept- browsing, based on a knowledge warehouse layer on top of a heterogeneous knowledge base with various systems interfaces. Such a concept browser will empower knowledge workers to interact with knowledge structures.

Interactive Segmentation of MR Images from Brain Tumor Patients

Medical doctors often do not trust the result of fully automatic segmentations because they have no possibility to make corrections if necessary. On the other hand, manual corrections can introduce a user bias. In this work, we propose to integrate the possibility for quick manual corrections into a fully automatic segmentation method for brain tumor images. This allows for necessary corrections while maintaining a high objectiveness. The underlying idea is similar to the well-known Grab-Cut algorithm, but here we combine decision forest classification with conditional random field regularization for interactive segmentation of 3D medical images. The approach has been evaluated by two different users on the BraTS2012 dataset. Accuracy and robustness improved compared to a fully automatic method and our interactive approach was ranked among the top performing methods. Time for computation including manual interaction was less than 10 minutes per patient, which makes it attractive for clinical use.

Interactive Diffraction from Biological Nanostructures

We describe a technique for interactive rendering of diffraction effects produced by biological nanostructures, such as snake skin surface gratings. Our approach uses imagery from atomic force microscopy that accurately captures the geometry of the nanostructures responsible for structural colouration, that is, colouration due to wave interference, in a variety of animals. We develop a rendering technique that constructs bidirectional reflection distribution functions (BRDFs) directly from the measured data and leverages pre-computation to achieve interactive performance. We demonstrate results of our approach using various shapes of the surface grating nanostructures. Finally, we evaluate the accuracy of our pre-computation-based technique and compare to a reference BRDF construction technique.

Loyal to the Game? Strategic Policy Representation in Mixed Electoral Systems

In Germany's compensatory mixed electoral system, alternative electoral routes lead into parliament. We study the relationship between candidates' electoral situations across both tiers and policy representation, fully accounting for candidate, party and district preferences in a multi-actor constellation and the exact electoral incentives for candidates to represent either the party or the district. The results (2009 Bundestag election data) yield evidence of an interactive effect of closeness of the district race and list safety on candidates' positioning between their party and constituency.

Timely Reporting and Interactive Visualization of Animal Health and Slaughterhouse Surveillance Data in Switzerland

The reporting of outputs from health surveillance systems should be done in a near real-time and interactive manner in order to provide decision makers with powerful means to identify, assess, and manage health hazards as early and efficiently as possible. While this is currently rarely the case in veterinary public health surveillance, reporting tools do exist for the visual exploration and interactive interrogation of health data. In this work, we used tools freely available from the Google Maps and Charts library to develop a web application reporting health-related data derived from slaughterhouse surveillance and from a newly established web-based equine surveillance system in Switzerland. Both sets of tools allowed entry-level usage without or with minimal programing skills while being flexible enough to cater for more complex scenarios for users with greater programing skills. In particular, interfaces linking statistical softwares and Google tools provide additional analytical functionality (such as algorithms for the detection of unusually high case occurrences) for inclusion in the reporting process. We show that such powerful approaches could improve timely dissemination and communication of technical information to decision makers and other stakeholders and could foster the early-warning capacity of animal health surveillance systems.