PG2016short

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https://diglib7.eg.org/handle/10.2312/2630931

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Optimized Route for Crowd Evacuation
(The Eurographics Association, 2016) Wong, Sai-Keung; Wang, Yu-Shuen; Tang, Pao-Kun; Tsai, Tsung-Yu; Eitan Grinspun and Bernd Bickel and Yoshinori Dobashi
An evacuation plan helps people move away from an area or a building. To achieve a fast evacuation, we present an algorithm to compute the optimal route for each local region. The idea is to reduce congestion and to maximize the number of evacuees arriving at exits in every time span. Our system considers the crowd distribution, exit locations, and corridor widths when determining the optimal routes. It also simulates crowd movements during the route optimization. To implement this idea, we expect that neighboring crowds who take different evacuation routes should arrive at respective exits nearly at the same time. If this is not the case, our system updates the routes of the slower crowds. Given that crowd simulation is non-linear, the optimal route is computed in an iterative manner. The process repeats until an optimal state is achieved. Experiment results demonstrate the feasibility of our evacuation route optimization.
Compressing Bidirectional Texture Functions via Tensor Train Decomposition
(The Eurographics Association, 2016) Ballester-Ripoll, Rafael; Pajarola, Renato; Eitan Grinspun and Bernd Bickel and Yoshinori Dobashi
Material reflectance properties play a central role in photorealistic rendering. Bidirectional texture functions (BTFs) can faithfully represent these complex properties, but their inherent high dimensionality (texture coordinates, color channels, view and illumination spatial directions) requires many coefficients to encode. Numerous algorithms based on tensor decomposition have been proposed for efficient compression of multidimensional BTF arrays, however, these prior methods still grow exponentially in size with the number of dimensions. We tackle the BTF compression problem with a different model, the tensor train (TT) decomposition. The main difference is that TT compression scales linearly with the input dimensionality and is thus much better suited for high-dimensional data tensors. Furthermore, it allows faster random-access texel reconstruction than the previous Tucker-based approaches. We demonstrate the performance benefits of the TT decomposition in terms of accuracy and visual appearance, compression rate and reconstruction speed.
PG 2016 Short Papers: Frontmatter
(Eurographics Association, 2016) Eitan Grinspun; Bernd Bickel; Yoshinori Dobashi;
Dynamic Skin Deformation Simulation Using Musculoskeletal Model and Soft Tissue Dynamics
(The Eurographics Association, 2016) Murai, Akihiko; Hong, Q. Youn; Yamane, Katsu; Hodgins, Jessica K.; Eitan Grinspun and Bernd Bickel and Yoshinori Dobashi
Deformation of skin and muscle is essential for bringing an animated character to life. This deformation is difficult to animate in a realistic fashion using traditional techniques because of the subtlety of the skin deformations that must move appropriately for the character design. In this paper, we present an algorithm that generates natural, dynamic, and detailed skin deformation (movement and jiggle) from joint angle data sequences. The algorithm consists of two steps: identification of parameters for a quasi-static muscle model using a musculoskeletal model and a short sequence of skin deformation data, and simulation of dynamic muscle and soft tissue deformation with quasi-static muscle shape and a mass-spring-damper system. We demonstrate our method using skeletal motion capture data of a subject (whose data is not used for training) to create appropriate skin deformations for muscle co-contraction and external impacts. Experimental results show that the simulated skin deformations are quantitatively and qualitatively similar to the measured actual skin deformations.
Local Detail Enhancement for Volume Rendering under Global Illumination
(The Eurographics Association, 2016) Zheng, Jinta; Zhang, Tianjin; Qin, Jing; Eitan Grinspun and Bernd Bickel and Yoshinori Dobashi
We present a novel method for realistic perception enhanced volume rendering. Compared with traditional lighting systems, that either tend to eliminate important local shapes and details in volume data or cannot offer interactive global illumination, our method can enhance the edges and curvatures within a volume under global illumination through a user-friendly interface. We first propose an interactive volumetric lighting model to both simulate scattering and enhance the local detail information. In this model, users only need to determine a key light source. Next, we propose a new cue to intensify the shape perception by enhancing the local edges and details. The cue can be pre-computed and thus we can still keep the rendering process running real-time. Experiments on a variety of volume data demonstrate that the proposed method can generate more details, and hence more realistic rendering results.
Modified Filtered Importance Sampling for Virtual Spherical Gaussian Lights
(The Eurographics Association, 2016) Tokuyoshi, Yusuke; Eitan Grinspun and Bernd Bickel and Yoshinori Dobashi
This paper proposes a modification of the filtered importance sampling (FIS) method, and improves the quality of virtual spherical Gaussian light (VSGL) based real-time glossy indirect illumination using this modification. The original FIS method produces large overlaps of and gaps between filtering kernels for high-frequency probability density functions (PDFs). This is because the size of the filtering kernel is determined using the PDF at the sampled center of the kernel. To reduce those overlaps and gaps, this paper determines the kernel size using the integral of the PDF in the filtering kernel. Our key insight is that these integrals are approximately constant, if kernel centers are sampled using stratified sampling. Therefore, an appropriate kernel size can be obtained by solving this integral equation. Using the proposed kernel size for FIS-based VSGL generation, undesirable artifacts are significantly reduced with a negligibly small overhead.
Reflectance and Shape Estimation for Cartoon Shaded Objects
(The Eurographics Association, 2016) Todo, Hideki; Yamaguchi, Yasushi; Eitan Grinspun and Bernd Bickel and Yoshinori Dobashi
Although many photorealistic relighting methods provide a way to change the illumination of objects in a digital photograph, it is currently difficult to relight a cartoon shading style in digital illustrations. The main difference between photorealistic and cartoon shading styles is that cartoon shading is characterized by soft color quantization and nonlinear color variations that cause noticeable reconstruction errors under a physical reflectance assumption such as Lambertian. To handle this nonphotorealistic shading property, we focus on the shading analysis of the most fundamental cartoon shading technique. Based on its color map shading representation, we propose a simple method to decompose the input shading to a smooth shape with a nonlinear reflectance property. We have conducted simple ground-truth evaluations to compare our results to those obtained by other approaches.
Viewpoint Selection for Taking a good Photograph of Architecture
(The Eurographics Association, 2016) He, Jingwu; Zhou, Wenzhe; Wang, Linbo; Zhang, Hongjie; Guo, Yanwen; Eitan Grinspun and Bernd Bickel and Yoshinori Dobashi
This paper studies the problem of how to choose the viewpoint for taking good photographs for architecture. We achieve this by learning from professional photographs of world famous landmarks that are available in the Internet. Unlike the previous efforts devoted to photo quality assessment which mainly rely on visual features, we show in this paper combining visual features with geometric features computed on the 3D models can result in a more reliable evaluation of viewpoint quality. Specifically, we collect a set of photographs for each of 6 world famous architectures as well as their 3D models from Internet. Viewpoint recovery for images is carried out by an image-model registration process, after which a newly proposed viewpoint clustering strategy is exploited to validate users' viewpoint preference when photographing landmarks. Finally, we extract a number of 2D and 3D features for each image based on multiple visual and geometric cues, and perform viewpoint recommendation by learning from both 2D and 3D features, achieving superior performance over using solely 2D or 3D features. We show the effectiveness of the proposed approach through extensive experiments.
Computational Design of Iris Folding Patterns
(The Eurographics Association, 2016) Igarashi, Yuki; Igarashi, Takeo; Mitani, Jun; Eitan Grinspun and Bernd Bickel and Yoshinori Dobashi
Iris folding is a motif consisting of layered strips of paper, forming a spiral pattern behind an aperture, which can be used to make cards and gift tags. This paper describes an interactive computational tool to assist in the design and construction of original iris folding patterns. The design of iris folding patterns is formulated as the calculation of a circumscribed polygonal sequence around a seed polygon. We analyzed the problem and found that it is possible to compute the positions of vertices analytically for regular polygon; however, it is not straightforward to do so for irregular polygons, and we used a numerical method for irregular polygons, which can be applied to arbitrary convex seed polygons. The user can experiment quickly with various patterns using the system prior to constructing the motif.
Interactive Multicut Video Segmentation
(The Eurographics Association, 2016) Levinkov, Evgeny; Tompkin, James; Bonneel, Nicolas; Kirchhoff, Steffen; Andres, Bjoern; Pfister, Hanspeter; Eitan Grinspun and Bernd Bickel and Yoshinori Dobashi
Video segmentation requires separating foreground from background, but the general problem extends to more complicated scene segmentations of different objects and their multiple parts. We develop a new approach to interactive multi-label video segmentation where many objects are segmented simultaneously with consistent spatio-temporal boundaries, based on intuitive multi-colored brush scribbles. From these scribbles, we derive constraints to define a combinatorial problem known as the multicut-a problem notoriously difficult and slow to solve. We describe a solution using efficient heuristics to make multi-label video segmentation interactive. As our solution generalizes typical binary segmentation tasks, while also improving efficiency in multi-label tasks, our work shows the promise of multicuts for interactive video segmentation.
Icon Set Selection via Human Computation
(The Eurographics Association, 2016) Laursen, Lasse Farnung; Koyama, Yuki; Chen, Hsiang-Ting; Garces, Elena; Gutierrez, Diego; Harper, Richard; Igarashi, Takeo; Eitan Grinspun and Bernd Bickel and Yoshinori Dobashi
Picking the best icons for a graphical user interface is difficult. We present a new method which, given several icon candidates representing functionality, selects a complete icon set optimized for comprehensibility and identifiability. These two properties are measured using human computation. We apply our method to a domain with a less established iconography and produce several icon sets. To evaluate our method, we conduct a user study comparing these icon sets and a designer-picked set. Our estimated comprehensibility score correlate with the percentage of correctly understood icons, and our method produces an icon set with a higher comprehensibility score than the set picked by an involved icon designer. The estimated identifiability score and related tests did not yield significant findings. Our method is easy to integrate in traditional icon design workflow and is intended for use by both icon designers, and clients of icon designers.

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