Die drei besten Artikel aus den »Selected Readings in Computer Graphics« des Jahres 2013 wurden mit dem Best Paper Award in den Kategorien »Impact on Business«, »Impact on Society« und »Impact on Science« ausgezeichnet. In die engere Wahl kamen weitere sechs Artikel.

Die Gewinner in den jeweiligen Kategorien sind:

Impact on Business

Landesberger, Tatiana von; Diel, Simon; Bremm,Sebastian; Fellner, Dieter W.:

Visual Analysis of Contagion in Networks

Impact on Society

Steger, Sebastian; Bozoglu, Y. Nazli; Kuijper, Arjan ; Wesarg, Stefan:

Application of Radial Ray Based Segmentation to Cervical Lymph Nodes in CT Images

Impact on Science

Schmidt, Uwe; Rother, Carsten; Nowozin, Sebastian; Jancsary, Jeremy; Roth, Stefan:

Discriminative Non-blind Deblurring

Liste der Publikationen

Gewinner und die Publikationen, die in die engere Wahl gekommen sind.

 

Große-Puppendahl, Tobias; Braun, Andreas; Kamieth, Felix; Kuijper, Arjan:
Swiss-Cheese Extended: An Object Recognition Method for Ubiquitous Interfaces based on Capacitive Proximity Sensing
2013
In: Bodker, Susanne (Ed.) et al.: CHI 2013. Changing Perspective : The 31st Annual CHI Conference on Human Factors in Computing Systems. New York: ACM Press, 2013, pp. 1401-1410
Conference on Human Factors in Computing Systems (CHI) <31, 2013, Paris, France>
Swiss-Cheese Extended proposes a novel real-time method for recognizing objects with capacitive proximity sensors. Applying this technique to ubiquitous user interfaces, it is possible to detect the 3D-position of multiple human hands in different configurations above a surface that is equipped with a small number of sensors. The retrieved object configurations can significantly improve a user's interaction experience or an application's execution context, for example by detecting multi-hand zoom and rotation gestures or recognizing a grasping hand. We emphasize the broad applicability of the proposed method with a study of a multi-hand gesture recognition device. Swiss-Cheese Extended proposes a novel real-time method for recognizing objects with capacitive proximity sensors. Applying this technique to ubiquitous user interfaces, it is possible to detect the 3D-position of multiple human hands in different configurations above a surface that is equipped with a small number of
sensors. The retrieved object configurations can significantly improve a user's interaction experience or an application's execution context, for example by detecting multi-hand zoom and rotation gestures or recognizing a grasping hand. We emphasize the broad applicability of the proposed method with a study of a multi-hand gesture recognition device.

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Kopf, Johannes; Langguth, Fabian; Scharstein, Daniel; Szeliski, Richard; Goesele, Michael:
Image-Based Rendering in the Gradient Domain
2013
In: ACM Transactions on Graphics, Vol.32 (2013), 6, pp. 199:1 - 199:9
Conference on Computer and Exhibition on Computer Graphics and Interactive Techniques in Asia (SIGGRAPH ASIA) <6, 2013, Hong Kong, China>
We propose a novel image-based rendering algorithm for handling complex scenes that may include reflective surfaces. Our key contribution lies in treating the problem in the gradient domain. We use a standard technique to estimate scene depth, but assign depths to image gradients rather than pixels. A novel view is obtained by rendering the horizontal and vertical gradients, from which the final result is reconstructed through Poisson integration using an approximate solution as a data term. Our algorithm is able to handle general scenes including reflections and similar effects without explicitly separating the scene into reflective and transmissive parts, as required by previous work. Our prototype renderer is fully implemented on the GPU and runs in real time on commodity hardware.

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Landesberger, Tatiana von; Diel, Simon; Bremm, Sebastian; Fellner, Dieter W.:
Visual Analysis of Contagion in Networks
2015
In: Information Visualization, Vol.14 (2015), 2, pp. 93-110. Published online before print May 28, 2013
Contagion is a process whereby the collapse of a node in a network leads to the collapse of neighboring nodes and thereby sets off a chain reaction in the network. It thus creates a special type of time-dependent network. Such processes are studied in various applications, for example, in financial network analysis, infection diffusion prediction, supply-chain management, or gene regulation. Visual analytics methods can help analysts examine contagion effects. For this purpose, network visualizations need to be complemented with specific features to illustrate the contagion process. Moreover, new visual analysis techniques for comparison of contagion need to be developed.

In this paper, we propose a system geared to the visual analysis of contagion. It includes the simulation of contagion effects as well as their visual exploration. We present new tools able to compare the evolution of the different contagion processes. In this way, propagation of disturbances can be effectively analyzed. We focus on financial networks; however, our system can be applied to other use cases as well.

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Milan, Anton; Schindler, Konrad; Roth, Stefan:
Detection- and Trajectory-Level Exclusion in Multiple Object Tracking
2013
In: IEEE Computer Society: IEEE Conference on Computer Vision and Pattern Recognition. Proceedings : CVPR 2013. Los Alamitos, Calif.: IEEE Computer Society Conference Publishing Services (CPS), 2013, pp. 3682-3689
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) <31, 2013, Portland, OR, USA>
When tracking multiple targets in crowded scenarios, modeling mutual exclusion between distinct targets becomes important at two levels: (1) in data association, each target observation should support at most one trajectory and each trajectory should be assigned at most one observation per frame; (2) in trajectory estimation, two trajectories should remain spatially separated at all times to avoid collisions. Yet, existing trackers often sidestep these important constraints. We address this using a mixed discrete-continuous conditional random field (CRF) that explicitly models both types of constraints: Exclusion between conflicting observations with supermodular pairwise terms, and exclusion between trajectories by generalizing global label costs to suppress the co-occurrence of incompatible labels (trajectories). We develop an expansion move-based MAP estimation scheme that handles both non-submodular constraints and pairwise global label costs. Furthermore, we perform a
statistical analysis of ground-truth trajectories to derive appropriate CRF potentials for modeling data fidelity, target dynamics, and inter-target occlusion.

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Schmidt, Uwe; Rother, Carsten; Nowozin, Sebastian; Jancsary, Jeremy; Roth, Stefan:
Discriminative Non-blind Deblurring
2013
In: IEEE Computer Society: IEEE Conference on Computer Vision and Pattern Recognition. Proceedings : CVPR 2013. Los Alamitos, Calif.: IEEE Computer Society Conference Publishing Services (CPS), 2013, pp. 604-611
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) <31, 2013, Portland, OR, USA>
Non-blind deblurring is an integral component of blind approaches for removing image blur due to camera shake. Even though learning-based deblurring methods exist, they have been limited to the generative case and are computationally expensive. To this date, manually-defined models are thus most widely used, though limiting the attained restoration quality. We address this gap by proposing a discriminative approach for non-blind deblurring. One key challenge is that the blur kernel in use at test time is not known in advance. To address this, we analyze existing approaches that use half-quadratic regularization. From this analysis, we derive a discriminative model cascade for image deblurring. Our cascade model consists of a Gaussian CRF at each stage, based on the recently introduced regression tree fields. We train our model by loss minimization and use synthetically generated blur kernels to generate training data. Our experiments show that the proposed approach is efficient
and yields state-of-the-art restoration quality on images corrupted with synthetic and real blur.

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Steger, Sebastian; Bozoglu, Y. Nazli; Kuijper, Arjan; Wesarg, Stefan:
Application of Radial Ray Based Segmentation to Cervical Lymph Nodes in CT Images
2013
In: IEEE Transactions on Medical Imagaing, Vol.32 (2013), 5, pp. 888-900
The 3D-segmentation of lymph nodes in CT images is required for staging and disease progression monitoring. Major challenges are shape and size variance, as well as low contrast, image noise, and pathologies.

In this paper, radial ray based segmentation is applied to lymph nodes: From a seed point, rays are cast into all directions and an optimization technique determines a radius for each ray based on image appearance and shape knowledge. Lymph node specific appearance cost functions are introduced and their optimal parameters are determined. For the first time, the resulting segmentation accuracy of different appearance cost functions and optimization strategies are compared. Further contributions are extensions to reduce the dependency on the seed point, to support a larger variety of shapes, and to enable interaction. The best results are obtained using graph-cut on a combination of the direction weighted image gradient and accumulated intensities outside a predefined intensity range. Evaluation on 100 lymph nodes shows that with an average symmetric surface distance of 0.41 mm the segmentation accuracy is close to manual segmentation and outperforms existing radial ray and model based
methods. The method's inter-observer-variability of 5.9% for volume assessment is lower than the 15.9% obtained using manual segmentation.

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Ullrich, Torsten; Silva, Nelson; Eggeling, Eva; Fellner, Dieter W.:
Generative Modeling and Numerical Optimization for Energy Efficient Buildings
2013
In: IEEE Industrials Electronics Society: IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society. Proceedings. New York: IEEE Press, 2013, pp. 4756-4761
Annual Conference of the IEEE Industrial Electronics Society (IECON) <39, 2013, Vienna, Austria>
A procedural model is a script, which generates a geometric object. The script's input parameters offer a simple way to specify and modify the scripting output. Due to its algorithmic character, a procedural model is perfectly suited to describe geometric shapes with well-organized structures and repetitive forms.

In this paper, we interpret a generative script as a function, which is nested into an objective function. Thus, the script's parameters can be optimized according to an objective. We demonstrate this approach using architectural examples: each generative script creates a building with several free parameters. The objective function is an energy-efficiency-simulation that approximates a building's annual energy consumption. Consequently, the nested objective function reads a set of building parameters and returns the energy needs for the corresponding building. This nested function is passed to a minimization and optimization process. Outcome is the best building (within the family of buildings described by its script) concerning energy-efficiency. Our contribution is a new way of modeling. The generative approach separates design and engineering: the complete design is encoded in a script and the script ensures that all parameter combinations (within a fixed range) generate a valid
design. Then the design can be optimized numerically.

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Wientapper, Folker; Wuest, Harald; Rojtberg, Pavel; Fellner, Dieter W.:
A Camera-Based Calibration for Automotive Augmented Reality Head-Up-Displays
2013
In: IEEE Computer Society Visualization and Graphics Technical Committee (VGTC): 12th IEEE International Symposium on Mixed and Augmented Reality 2013. : ISMAR 2013. Los Alamitos, Calif.: IEEE Computer Society, 2013, pp. 189-197
IEEE International Symposium on Mixed and Augmented Reality (ISMAR) <12, 2013, Adelaide, SA, Australia>
Using Head-up-Displays (HUD) for Augmented Reality requires to have an accurate internal model of the image generation process, so that 3D content can be visualized perspectively correct from the viewpoint of the user. We present a generic and cost-effective camera-based calibration for an automotive HUD which uses the windshield as a combiner. Our proposed calibration model encompasses the view-independent spatial geometry, i.e. the exact location, orientation and scaling of the virtual plane, and a view-dependent image warping transformation for correcting the distortions caused by the optics and the irregularly curved windshield. View-dependency is achieved by extending the classical polynomial distortion model for cameras and projectors to a generic five-variate mapping with the head position of the viewer as additional input. The calibration involves the capturing of an image sequence from varying viewpoints, while displaying a known target pattern on the HUD. The accurate
registration of the camera path is retrieved with state-of-the-art vision-based tracking. As all necessary data is acquired directly from the images, no external tracking equipment needs to be installed. After calibration, the HUD can be used together with a head-tracker to form a head-coupled display which ensures a perspectively correct rendering of any 3D object in vehicle coordinates from a large range of possible viewpoints. We evaluate the accuracy of our model quantitatively and qualitatively.

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Zmugg, René; Thaller, Wolfgang; Krispel, Ulrich; Edelsbrunner, Johannes; Havemann, Sven; Fellner, Dieter W.:
Procedural Architecture Using Deformation-aware Split Grammars
2014
In: The Visual Computer, Vol.30 (2014), 9, pp. 1009-1019. Published online: 29 December 2013
With the current state of video games growing in scale, manual content creation may no longer be feasible in the future. Split grammars are a promising technology for large-scale procedural generation of urban structures, which are very common in video games. Buildings with curved parts, however, can currently only be approximated by static pre-modelled assets, and rules apply only to planar surface parts. We present an extension to split grammar systems that allow the creation of curved architecture through integration of free-form deformations at any level in a grammar. Further split rules can then proceed in two different ways. They can either adapt to these deformations so that repetitions can adjust to more or less space, while maintaining length constraints, or they can split the deformed geometry with straight planes to introduce straight structures on deformed geometry.

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