bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and fabrication by example
Authors: Schulz Adriana , Shamir Ariel , Levin David I. W. , Sitthi-amorn Pitchaya , Matusik Wojciech
Published: July 2014

We propose a data-driven method for designing 3D models that can be fabricated. First, our approach converts a collection of expert-created designs to a dataset of parameterized design templates that includes all information necessary for fabrication. The templates are then used in an interactive design system to create new fabri-cable models in a design-by-example manner. A simple interface allows novice users to choose template parts from the database, change their parameters, and combine them to create new models. Using the information in the template database, the system can automatically position, align, and connect parts: the system accomplishes this by adjusting parameters, adding appropriate constraints, and assigning connectors. This process ensures that the created models can be fabricated, saves the user from many tedious but necessary tasks, and makes it possible for non-experts to design and create actual physical objects. To demonstrate our data-driven method, we present several examples of complex functional objects that we designed and manufactured using our system.
True2Form
Authors: Xu Baoxuan , Chang William , Sheffer Alla , Bousseau Adrien , McCrae James , Singh Karan
Published: July 2014

True2Formis a sketch-based modeling system that reconstructs 3D curves from typical design sketches. Our approach to infer 3D form from 2D drawings is a novel mathematical framework of insights derived from perception and design literature. We note that designers favor viewpoints that maximally reveal 3D shape information, and strategically sketch descriptive curves that convey intrinsic shape properties, such as curvature, symmetry, or parallelism. Studies indicate that viewers apply these properties selectively to envision a globally consistent 3D shape. We mimic this selective regularization algorithmically, by progressively detecting and enforcing applicable properties, accounting for their global impact on an evolving 3D curve network. Balancing regularity enforcement against sketch fidelity at each step allows us to correct for inaccuracy inherent in free-hand sketching. We perceptually validate our approach by showing agreement between our algorithm and viewers in selecting applicable regularities. We further evaluate our solution by: reconstructing a range of 3D models from diversely sourced sketches; comparisons to prior art; and visual comparison to both ground-truth and 3D reconstructions by designers.
Capturing and stylizing hair for 3D fabrication
Authors: Echevarria Jose I. , Bradley Derek , Gutierrez Diego , Beeler Thabo
Published: July 2014

Recently, we have seen a growing trend in the design and fabrication of personalized figurines, created by scanning real people and then physically reproducing miniature statues with 3D printers. This is currently a hot topic both in academia and industry, and the printed figurines are gaining more and more realism, especially with state-of-the-art facial scanning technology improving. However, current systems all contain the same limitation - no previous method is able to suitably capture personalized
hair-styles
for physical reproduction. Typically, the subject's hair is approximated very coarsely or replaced completely with a template model. In this paper we present the first method for
stylized
hair capture, a technique to reconstruct an individual's actual hair-style in a manner suitable for physical reproduction. Inspired by centuries-old artistic sculptures, our method generates hair as a closed-manifold surface, yet contains the structural and color elements stylized in a way that captures the defining characteristics of the hair-style. The key to our approach is a novel multi-view stylization algorithm, which extends feature-preserving color filtering from 2D images to irregular manifolds in 3D, and introduces abstract geometric details that are coherent with the color stylization. The proposed technique fits naturally in traditional pipelines for figurine reproduction, and we demonstrate the robustness and versatility of our approach by capturing several subjects with widely varying hair-styles.
Color map optimization for 3D reconstruction with consumer depth cameras
Authors: Zhou Qian-Yi , Koltun Vladlen
Published: July 2014

We present a global optimization approach for mapping color images onto geometric reconstructions. Range and color videos produced by consumer-grade RGB-D cameras suffer from noise and optical distortions, which impede accurate mapping of the acquired color data to the reconstructed geometry. Our approach addresses these sources of error by optimizing camera poses in tandem with non-rigid correction functions for all images. All parameters are optimized jointly to maximize the photometric consistency of the reconstructed mapping. We show that this optimization can be performed efficiently by an alternating optimization algorithm that interleaves analytical updates of the color map with decoupled parameter updates for all images. Experimental results demonstrate that our approach substantially improves color mapping fidelity.
Multiplexed metropolis light transport
Authors: Hachisuka Toshiya , Kaplanyan Anton S. , Dachsbacher Carsten
Published: July 2014

Global illumination algorithms using Markov chain Monte Carlo (MCMC) sampling are well-known for their efficiency in scenes with complex light transport. Samples in such algorithms are generated as a history of Markov chain states so that they are distributed according to the contributions to the image. The whole process is done based only on the information of the path contributions and user-defined transition probabilities from one state to the others. In light transport simulation, however, there is more information that can be used to improve the efficiency of path sampling. A notable example is
multiple importance sampling
(MIS) in bidirectional path tracing, which utilizes the probability densities of constructing a given path with different estimators. While MIS is a powerful ordinary Monte Carlo method, how to incorporate such additional information into MCMC sampling has been an open problem. We introduce a novel MCMC sampling framework,
primary space serial tempering
, which fuses the ideas of MCMC sampling and MIS for the first time. The key idea is to explore not only the sample space using a Markov chain, but also different estimators to generate samples by utilizing the information already available for MIS. Based on this framework, we also develop a novel rendering algorithm,
multiplexed Metropolis light transport
, which automatically and adaptively constructs paths with appropriate techniques as predicted by MIS. The final algorithm is very easy to implement, yet in many cases shows comparable (or even better) performance than significantly more complex MCMC rendering algorithms.
A comprehensive framework for rendering layered materials
Authors: Jakob Wenzel , d'Eon Eugene , Jakob Otto , Marschner Steve
Published: July 2014

We present a general and practical method for computing BSDFs of layered materials. Its ingredients are transport-theoretical models of isotropic or anisotropic scattering layers and smooth or rough boundaries of conductors and dielectrics. Following expansion into a directional basis that supports arbitrary composition, we are able to efficiently and accurately synthesize BSDFs for a great variety of layered structures.

Reflectance models created by our system correctly account for multiple scattering within and between layers, and in the context of a rendering system they are efficient to evaluate and support texturing and exact importance sampling. Although our approach essentially involves tabulating reflectance functions in a Fourier basis, the generated models are compact to store due to the inherent sparsity of our representation, and are accurate even for narrowly peaked functions. While methods for rendering general layered surfaces have been investigated in the past, ours is the first system that supports arbitrary layer structures while remaining both efficient and accurate.

We validate our model by comparing to measurements of real-world examples of layered materials, and we demonstrate an interactive visual design tool that enables easy exploration of the space of layered materials. We provide a fully practical, high-performance implementation in an open-source rendering system.
A compressive light field projection system
Authors: Hirsch Matthew , Wetzstein Gordon , Raskar Ramesh
Published: July 2014

For about a century, researchers and experimentalists have strived to bring glasses-free 3D experiences to the big screen. Much progress has been made and light field projection systems are now commercially available. Unfortunately, available display systems usually employ dozens of devices making such setups costly, energy inefficient, and bulky. We present a compressive approach to light field synthesis with projection devices. For this purpose, we propose a novel, passive screen design that is inspired by angle-expanding Keplerian telescopes. Combined with high-speed light field projection and nonnegative light field factorization, we demonstrate that compressive light field projection is possible with a single device. We build a prototype light field projector and angle-expanding screen from scratch, evaluate the system in simulation, present a variety of results, and demonstrate that the projector can alternatively achieve super-resolved and high dynamic range 2D image display when used with a conventional screen.
AverageExplorer
Authors: Zhu Jun-Yan , Lee Yong Jae , Efros Alexei A.
Published: July 2014

This paper proposes an interactive framework that allows a user to rapidly explore and visualize a large image collection using the medium of
average images
. Average images have been gaining popularity as means of artistic expression and data visualization, but the creation of compelling examples is a surprisingly laborious and manual process. Our interactive, real-time system provides a way to summarize large amounts of visual data by
weighted
average(s) of an image collection, with the weights reflecting user-indicated importance. The aim is to capture not just the mean of the distribution, but a set of modes discovered via interactive exploration. We pose this exploration in terms of a user interactively "editing" the average image using various types of strokes, brushes and warps, similar to a normal image editor, with each user interaction providing a new constraint to update the average. New weighted averages can be spawned and edited either individually or jointly. Together, these tools allow the user to simultaneously perform two fundamental operations on visual data: user-guided clustering and user-guided alignment, within the same framework. We show that our system is useful for various computer vision and graphics applications.
Modeling and optimizing eye vergence response to stereoscopic cuts
Authors: Templin Krzysztof , Didyk Piotr , Myszkowski Karol , Hefeeda Mohamed M. , Seidel Hans-Peter , Matusik Wojciech
Published: July 2014

Sudden temporal depth changes, such as cuts that are introduced by video edits, can significantly degrade the quality of stereoscopic content. Since usually not encountered in the real world, they are very challenging for the audience. This is because the eye vergence has to constantly adapt to new disparities in spite of conflicting accommodation requirements. Such rapid disparity changes may lead to confusion, reduced understanding of the scene, and overall attractiveness of the content. In most cases the problem cannot be solved by simply matching the depth around the transition, as this would require flattening the scene completely. To better understand this limitation of the human visual system, we conducted a series of eye-tracking experiments. The data obtained allowed us to derive and evaluate a model describing adaptation of vergence to disparity changes on a stereoscopic display. Besides computing user-specific models, we also estimated parameters of an average observer model. This enables a range of strategies for minimizing the adaptation time in the audience.
Rendering glints on high-resolution normal-mapped specular surfaces
Authors: Yan Ling-Qi , Hašan Miloš , Jakob Wenzel , Lawrence Jason , Marschner Steve , Ramamoorthi Ravi
Published: July 2014

Complex specular surfaces under sharp point lighting show a fascinating glinty appearance, but rendering it is an unsolved problem. Using Monte Carlo pixel sampling for this purpose is impractical: the energy is concentrated in tiny highlights that take up a minuscule fraction of the pixel. We instead compute an accurate solution using a completely different deterministic approach. Our method considers the true distribution of normals on a surface patch seen through a single pixel, which can be highly complex. We show how to evaluate this distribution efficiently, assuming a Gaussian pixel footprint and Gaussian intrinsic roughness. We also take advantage of hierarchical pruning of position-normal space to rapidly find texels that might contribute to a given normal distribution evaluation. Our results show complex, temporally varying glints from materials such as bumpy plastics, brushed and scratched metals, metallic paint and ocean waves.
Estimating image depth using shape collections
Authors: Su Hao , Huang Qixing , Mitra Niloy J. , Li Yangyan , Guibas Leonidas
Published: July 2014

Images, while easy to acquire, view, publish, and share, they lack critical depth information. This poses a serious bottleneck for many image manipulation, editing, and retrieval tasks. In this paper we consider the problem of adding depth to an image of an object, effectively 'lifting' it back to 3D, by exploiting a collection of aligned 3D models of related objects. Our key insight is that, even when the imaged object is not contained in the shape collection, the network of shapes implicitly characterizes a shape-specific deformation subspace that regularizes the problem and enables robust diffusion of depth information from the shape collection to the input image. We evaluate our fully automatic approach on diverse and challenging input images, validate the results against Kinect depth readings, and demonstrate several imaging applications including depth-enhanced image editing and image relighting.
Inverse procedural modeling of facade layouts
Authors: Wu Fuzhang , Yan Dong-Ming , Dong Weiming , Zhang Xiaopeng , Wonka Peter
Published: July 2014

In this paper, we address the following research problem: How can we generate a meaningful split grammar that explains a given facade layout? To evaluate if a grammar is meaningful, we propose a cost function based on the description length and minimize this cost using an approximate dynamic programming framework. Our evaluation indicates that our framework extracts meaningful split grammars that are competitive with those of expert users, while some users and all competing automatic solutions are less successful.
Floating scale surface reconstruction
Authors: Fuhrmann Simon , Goesele Michael
Published: July 2014

Any sampled point acquired from a real-world geometric object or scene represents a finite surface area and not just a single surface point. Samples therefore have an inherent scale, very valuable information that has been crucial for high quality reconstructions. We introduce a new method for surface reconstruction from oriented, scale-enabled sample points which operates on large, redundant and potentially noisy point sets. The approach draws upon a simple yet efficient mathematical formulation to construct an implicit function as the sum of compactly supported basis functions. The implicit function has spatially continuous "floating" scale and can be readily evaluated without any preprocessing. The final surface is extracted as the zero-level set of the implicit function. One of the key properties of the approach is that it is virtually parameter-free even for complex, mixed-scale datasets. In addition, our method is easy to implement, scalable and does not require any global operations. We evaluate our method on a wide range of datasets for which it compares favorably to popular classic and current methods.
Detailed water with coarse grids
Authors: Edwards Essex , Bridson Robert
Published: July 2014

We present a new adaptive fluid simulation method that captures a high resolution surface with precise dynamics, without an inefficient fine discretization of the entire fluid volume. Prior adaptive methods using octrees or unstructured meshes carry large overheads and implementation complexity. We instead stick with coarse regular Cartesian grids, using detailed cut cells at boundaries, and discretize the dynamics with a p-adaptive Discontinuous Galerkin (DG) method. This retains much of the data structure simplicity of regular grids, more efficiently captures smooth parts of the flow, and offers the flexibility to easily increase resolving power where needed without geometric refinement.
Continuous projection for fast
L
1
reconstruction
Authors: Preiner Reinhold , Mattausch Oliver , Arikan Murat , Pajarola Renato , Wimmer Michael
Published: July 2014

With better and faster acquisition devices comes a demand for fast robust reconstruction algorithms, but no
L
1
-based technique has been fast enough for online use so far. In this paper, we present a novel continuous formulation of the weighted locally optimal projection (WLOP) operator based on a Gaussian mixture describing the input point density. Our method is up to 7 times faster than an optimized GPU implementation of WLOP, and achieves interactive frame rates for moderately sized point clouds. We give a comprehensive quality analysis showing that our continuous operator achieves a generally higher reconstruction quality than its discrete counterpart. Additionally, we show how to apply our continuous formulation to spherical mixtures of normal directions, to also achieve a fast robust normal reconstruction.
Darkroom
Authors: Hegarty James , Brunhaver John , DeVito Zachary , Ragan-Kelley Jonathan , Cohen Noy , Bell Steven , Vasilyev Artem , Horowitz Mark , Hanrahan Pat
Published: July 2014

Specialized image signal processors (ISPs) exploit the structure of image processing pipelines to minimize memory bandwidth using the architectural pattern of
line-buffering
, where all intermediate data between each stage is stored in small on-chip buffers. This provides high energy efficiency, allowing long pipelines with tera-op/sec. image processing in battery-powered devices, but traditionally requires painstaking manual design in hardware. Based on this pattern, we present Darkroom, a language and compiler for image processing. The semantics of the Darkroom language allow it to compile programs directly into line-buffered pipelines, with all intermediate values in local line-buffer storage, eliminating unnecessary communication with off-chip DRAM. We formulate the problem of optimally scheduling line-buffered pipelines to minimize buffering as an integer linear program. Finally, given an optimally scheduled pipeline, Darkroom synthesizes hardware descriptions for ASIC or FPGA, or fast CPU code. We evaluate Darkroom implementations of a range of applications, including a camera pipeline, low-level feature detection algorithms, and deblurring. For many applications, we demonstrate gigapixel/sec. performance in under 0.5mm
2
of ASIC silicon at 250 mW (simulated on a 45nm foundry process), real-time 1080p/60 video processing using a fraction of the resources of a modern FPGA, and tens of megapixels/sec. of throughput on a quad-core x86 processor.
Eigenmode compression for modal sound models
Authors: Langlois Timothy R. , An Steven S. , Jin Kelvin K. , James Doug L.
Published: July 2014

We propose and evaluate a method for significantly compressing modal sound models, thereby making them far more practical for audiovisual applications. The dense eigenmode matrix, needed to compute the sound model's response to contact forces, can consume tens to thousands of megabytes depending on mesh resolution and mode count. Our eigenmode compression pipeline is based on non-linear optimization of Moving Least Squares (MLS) approximations. Enhanced compression is achieved by exploiting symmetry both within and between eigenmodes, and by adaptively assigning per-mode error levels based on human perception of the far-field pressure amplitudes. Our method provides smooth eigenmode approximations, and efficient random access. We demonstrate that, in many cases, hundredfold compression ratios can be achieved without audible degradation of the rendered sound.
Simulating articulated subspace self-contact
Authors: Teng Yun , Otaduy Miguel A. , Kim Theodore
Published: July 2014

We present an efficient new subspace method for simulating the self-contact of articulated deformable bodies, such as characters. Self-contact is highly structured in this setting, as the limited space of possible articulations produces a predictable set of coherent collisions. Subspace methods can leverage this coherence, and have been used in the past to accelerate the collision detection stage of contact simulation. We show that these methods can be used to accelerate the
entire
contact computation, and allow self-contact to be resolved
without looking at all of the contact points
. Our analysis of the problem yields a broader insight into the types of non-linearities that subspace methods can efficiently approximate, and leads us to design a
pose-space cubature
scheme. Our algorithm accelerates self-contact by up to an order of magnitude over other subspace simulations, and accelerates the overall simulation by two orders of magnitude over full-rank simulations. We demonstrate the simulation of high resolution (100K -- 400K elements) meshes in self-contact at interactive rates (5.8 -- 50 FPS).
Rigid stabilization of facial expressions
Authors: Beeler Thabo , Bradley Derek
Published: July 2014

Facial scanning has become the industry-standard approach for creating digital doubles in movies and video games. This involves capturing an actor while they perform different expressions that span their range of facial motion. Unfortunately, the scans typically contain a superposition of the desired expression on top of un-wanted rigid head movement. In order to extract true expression deformations, it is essential to factor out the rigid head movement for each expression, a process referred to as
rigid stabilization
. In order to achieve production-quality in industry, face stabilization is usually performed through a tedious and error-prone manual process. In this paper we present the first automatic face stabilization method that achieves professional-quality results on large sets of facial expressions. Since human faces can undergo a wide range of deformation, there is not a single point on the skin surface that moves rigidly with the underlying skull. Consequently, computing the rigid transformation from direct observation, a common approach in previous methods, is error prone and leads to inaccurate results. Instead, we propose to indirectly stabilize the expressions by explicitly aligning them to an estimate of the underlying skull using anatomically-motivated constraints. We show that the proposed method not only outperforms existing techniques but is also on par with manual stabilization, yet requires less than a second of computation time.
Look over here
Authors: Cao Ying , Lau Rynson W. H. , Chan Antoni B.
Published: July 2014

Picture subjects and text balloons are basic elements in comics, working together to propel the story forward. Japanese comics artists often leverage a carefully designed composition of subjects and balloons (generally referred to as
panel elements
) to provide a continuous and fluid reading experience. However, such a composition is hard to produce for people without the required experience and knowledge. In this paper, we propose an approach for novices to synthesize a composition of panel elements that can effectively guide the reader's attention to convey the story. Our primary contribution is a probabilistic graphical model that describes the relationships among the artist's guiding path, the panel elements, and the viewer attention, which can be effectively learned from a small set of existing manga pages. We show that the proposed approach can measurably improve the readability, visual appeal, and communication of the story of the resulting pages, as compared to an existing method. We also demonstrate that the proposed approach enables novice users to create higher-quality compositions with less time, compared with commercially available programs.
Parametric wave field coding for precomputed sound propagation
Authors: Raghuvanshi Nikunj , Snyder John
Published: July 2014

The acoustic wave field in a complex scene is a chaotic 7D function of time and the positions of source and listener, making it difficult to compress and interpolate. This hampers precomputed approaches which tabulate impulse responses (IRs) to allow immersive, real-time sound propagation in static scenes. We code the field of time-varying IRs in terms of a few perceptual parameters derived from the IR's energy decay. The resulting parameter fields are spatially smooth and compressed using a lossless scheme similar to PNG. We show that this encoding removes two of the seven dimensions, making it possible to handle large scenes such as entire game maps within 100MB of memory. Run-time decoding is fast, taking 100
μ
s per source. We introduce an efficient and scalable method for convolutionally rendering acoustic parameters that generates artifact-free audio even for fast motion and sudden changes in reverberance. We demonstrate convincing spatially-varying effects in complex scenes including occlusion/obstruction and reverberation, in our system integrated with Unreal Engine 3
™
.
Meta-representation of shape families
Authors: Fish Noa , Averkiou Melinos , van Kaick Oliver , Sorkine-Hornung Olga , Cohen-Or Daniel , Mitra Niloy J.
Published: July 2014

We introduce a meta-representation that represents the
essence
of a family of shapes. The meta-representation learns the configurations of shape parts that are common across the family, and encapsulates this knowledge with a system of geometric distributions that encode relative arrangements of parts. Thus, instead of predefined priors, what characterizes a shape family is directly learned from the set of input shapes. The meta-representation is constructed from a set of co-segmented shapes with known correspondence. It can then be used in several applications where we seek to preserve the identity of the shapes as members of the family. We demonstrate applications of the meta-representation in exploration of shape repositories, where interesting shape configurations can be examined in the set; guided editing, where models can be edited while maintaining their familial traits; and coupled editing, where several shapes can be collectively deformed by directly manipulating the distributions in the meta-representation. We evaluate the efficacy of the proposed representation on a variety of shape collections.
Proactive 3D scanning of inaccessible parts
Authors: Yan Feilong , Sharf Andrei , Lin Wenzhen , Huang Hui , Chen Baoquan
Published: July 2014

The evolution of 3D scanning technologies have revolutionized the way real-world object are digitally acquired. Nowadays, high-definition and high-speed scanners can capture even large scale scenes with very high accuracy. Nevertheless, the acquisition of complete 3D objects remains a bottleneck, requiring to carefully sample the whole object's surface, similar to a coverage process. Holes and undersampled regions are common in 3D scans of complex-shaped objects with self occlusions and hidden interiors. In this paper we introduce the novel paradigm of
proactive scanning
, in which the user actively modifies the scene while scanning it, in order to reveal and access occluded regions. We take a holistic approach and integrate the user interaction into the continuous scanning process. Our algorithm allows for dynamic modifications of the scene as part of a global 3D scanning process. We utilize a scan registration algorithm to compute motion trajectories and separate between user modifications and other motions such as (hand-held) camera movements and small deformations. Thus, we reconstruct together the static parts into a complete unified 3D model. We evaluate our technique by scanning and reconstructing 3D objects and scenes consisting of inaccessible regions such as interiors, entangled plants and clutter.
genBRDF
Authors: Brady Adam , Lawrence Jason , Peers Pieter , Weimer Westley
Published: July 2014

We present a framework for learning new analytic BRDF models through Genetic Programming that we call genBRDF. This approach to reflectance modeling can be seen as an extension of traditional methods that rely either on a phenomenological or empirical process. Our technique augments the human effort involved in deriving mathematical expressions that accurately characterize complex high-dimensional reflectance functions through a large-scale optimization. We present a number of analysis tools and data visualization techniques that are crucial to sifting through the large result sets produced by genBRDF in order to identify fruitful expressions. Additionally, we highlight several new models found by genBRDF that have not previously appeared in the BRDF literature. These new BRDF models are compact and more accurate than current state-of-the-art alternatives.
Self-refining games using player analytics
Authors: Stanton Matt , Humberston Ben , Kase Brandon , O'Brien James F. , Fatahalian Kayvon , Treuille Adrien
Published: July 2014

Data-driven simulation demands good training data drawn from a vast space of possible simulations. While fully sampling these large spaces is infeasible, we observe that in practical applications, such as gameplay, users explore only a vanishingly small subset of the dynamical state space. In this paper we present a sampling approach that takes advantage of this observation by concentrating precomputation around the states that users are most likely to encounter. We demonstrate our technique in a prototype
self-refining game
whose dynamics improve with play, ultimately providing realistically rendered, rich fluid dynamics in real time on a mobile device. Our results show that our analytics-driven training approach yields lower model error and fewer visual artifacts than a heuristic training strategy.
Embree
Authors: Wald Ingo , Woop Sven , Benthin Carsten , Johnson Gregory S. , Ernst Manfred
Published: July 2014

We describe Embree, an open source ray tracing framework for x86 CPUs. Embree is explicitly designed to achieve high performance in professional rendering environments in which complex geometry and incoherent ray distributions are common. Embree consists of a set of low-level kernels that maximize utilization of modern CPU architectures, and an API which enables these kernels to be used in existing renderers with minimal programmer effort. In this paper, we describe the design goals and software architecture of Embree, and show that for secondary rays in particular, the performance of Embree is competitive with (and often higher than) existing state-of-the-art methods on CPUs and GPUs.
EZ-sketching
Authors: Su Qingkun , Li Wing Ho Andy , Wang Jue , Fu Hongbo
Published: July 2014

We present a new image-guided drawing interface called
EZ-Sketching
, which uses a tracing paradigm and automatically corrects sketch lines roughly traced over an image by analyzing and utilizing the image features being traced. While previous edge snapping methods aim at optimizing individual strokes, we show that a co-analysis of multiple roughly placed nearby strokes better captures the user's intent. We formulate automatic sketch improvement as a three-level optimization problem and present an efficient solution to it. EZ-Sketching can tolerate errors from various sources such as indirect control and inherently inaccurate input, and works well for sketching on touch devices with small screens using fingers. Our user study confirms that the drawings our approach helped generate show closer resemblance to the traced images, and are often aesthetically more pleasing.
Image completion using planar structure guidance
Authors: Huang Jia-Bin , Kang Sing Bing , Ahuja Narendra , Kopf Johannes
Published: July 2014

We propose a method for automatically guiding patch-based image completion using mid-level structural cues. Our method first estimates planar projection parameters, softly segments the known region into planes, and discovers translational regularity
within
these planes. This information is then converted into soft constraints for the low-level completion algorithm by defining prior probabilities for patch offsets and transformations. Our method handles multiple planes, and in the absence of any detected planes falls back to a baseline fronto-parallel image completion algorithm. We validate our technique through extensive comparisons with state-of-the-art algorithms on a variety of scenes.
Controllable high-fidelity facial performance transfer
Authors: Xu Feng , Chai Jinxiang , Liu Yilong , Tong Xin
Published: July 2014

Recent technological advances in facial capture have made it possible to acquire high-fidelity 3D facial performance data with stunningly high spatial-temporal resolution. Current methods for facial expression transfer, however, are often limited to large-scale facial deformation. This paper introduces a novel facial expression transfer and editing technique for high-fidelity facial performance data. The key idea of our approach is to decompose high-fidelity facial performances into high-level facial feature lines, large-scale facial deformation and fine-scale motion details and transfer them appropriately to reconstruct the retargeted facial animation in an efficient optimization framework. The system also allows the user to quickly modify and control the retargeted facial sequences in the spatial-temporal domain. We demonstrate the power of our approach by transferring and editing high-fidelity facial animation data from high-resolution source models to a wide range of target models, including both human faces and non-human faces such as "monster" and "dog".
Active volumetric musculoskeletal systems
Authors: Fan Ye , Litven Joshua , Pai Dinesh K.
Published: July 2014

We introduce a new framework for simulating the dynamics of musculoskeletal systems, with volumetric muscles in close contact and a novel data-driven muscle activation model. Muscles are simulated using an Eulerian-on-Lagrangian discretization that handles volume preservation, large deformation, and close contact between adjacent tissues. Volume preservation is crucial for accurately capturing the dynamics of muscles and other biological tissues. We show how to couple the dynamics of soft tissues with Lagrangian multi-body dynamics simulators, which are widely available. Our physiologically based muscle activation model utilizes knowledge of the active shapes of muscles, which can be easily obtained from medical imaging data or designed to meet artistic needs. We demonstrate results with models derived from MRI data and models designed for artistic effect.
High-order diffraction and diffuse reflections for interactive sound propagation in large environments
Authors: Schissler Carl , Mehra Ravish , Manocha Dinesh
Published: July 2014

We present novel algorithms for modeling interactive diffuse reflections and higher-order diffraction in large-scale virtual environments. Our formulation is based on ray-based sound propagation and is directly applicable to complex geometric datasets. We use an incremental approach that combines radiosity and path tracing techniques to iteratively compute diffuse reflections. We also present algorithms for wavelength-dependent simplification and visibility graph computation to accelerate higher-order diffraction at runtime. The overall system can generate plausible sound effects at interactive rates in large, dynamic scenes that have multiple sound sources. We highlight the performance in complex indoor and outdoor environments and observe an order of magnitude performance improvement over previous methods.
Space-time editing of elastic motion through material optimization and reduction
Authors: Li Siwang , Huang Jin , de Goes Fernando , Jin Xiaogang , Bao Hujun , Desbrun Mathieu
Published: July 2014

We present a novel method for elastic animation editing with space-time constraints. In a sharp departure from previous approaches, we not only optimize control forces added to a linearized dynamic model, but also optimize material properties to better match user constraints and provide plausible and consistent motion. Our approach achieves efficiency and scalability by performing all computations in a reduced rotation-strain (RS) space constructed with both cubature and geometric reduction, leading to two orders of magnitude improvement over the original RS method. We demonstrate the utility and versatility of our method in various applications, including motion editing, pose interpolation, and estimation of material parameters from existing animation sequences.
Learning to be a depth camera for close-range human capture and interaction
Authors: Fanello Sean Ryan , Keskin Cem , Izadi Shahram , Kohli Pushmeet , Kim David , Sweeney David , Criminisi Antonio , Shotton Jamie , Kang Sing Bing , Paek Tim
Published: July 2014

We present a machine learning technique for estimating absolute, per-pixel depth using any conventional monocular 2D camera, with minor hardware modifications. Our approach targets close-range human capture and interaction where dense 3D estimation of hands and faces is desired. We use hybrid classification-regression forests to
learn
how to map from near infrared intensity images to
absolute
, metric depth in real-time. We demonstrate a variety of human-computer interaction and capture scenarios. Experiments show an accuracy that outperforms a conventional light fall-off baseline, and is comparable to high-quality consumer depth cameras, but with a dramatically reduced cost, power consumption, and form-factor.
Trust Prediction via Belief Propagation
Authors: Zhang Richong , Mao Yongyi
Published: July 2014

The prediction of trust relationships in social networks plays an important role in the analytics of the networks. Although various link prediction algorithms for general networks may be adapted for this purpose, the recent notion of “trust propagation” has been shown to effectively capture the trust-formation mechanisms and resulted in an effective prediction algorithm. This article builds on the concept of trust propagation and presents a probabilistic trust propagation model. Our model exploits the modern framework of probabilistic graphical models, more specifically, factor graphs. Under this model, the trust prediction problem can be formulated as a statistical inference problem and we derive the belief propagation algorithm as a solver for trust prediction. The model and algorithm are tested using datasets from Epinions and Ciao, by which performance advantages over the previous algorithms are demonstrated.
Content-Based Video Copy Detection Benchmarking at TRECVID
Authors: Awad George , Over Paul , Kraaij Wessel
Published: July 2014

This article presents an overview of the video copy detection benchmark which was run over a period of 4 years (2008--2011) as part of the TREC Video Retrieval (TRECVID) workshop series. The main contributions of the article include i) an examination of the evolving design of the evaluation framework and its components (system tasks, data, measures); ii) a high-level overview of results and best-performing approaches; and iii) a discussion of lessons learned over the four years. The content-based copy detection (CCD) benchmark worked with a large collection of synthetic queries, which is atypical for TRECVID, as was the use of a normalized detection cost framework. These particular evaluation design choices are motivated and appraised.
Deadline-Constrained Clustered Scheduling for VLIW Architectures using Power-Gated Register Files
Authors: Liang Zhibin , Zhang Wei , Ma Yung-Cheng
Published: July 2014

Designing energy-efficient Digital Signal Processor (DSP) cores has become a key concern in embedded systems development. This paper proposes an energy-proportional computing scheme for Very Long Instruction Word (VLIW) architectures. To make the processor power scales with adapted parallelism, we propose incorporating distributed Power-Gated Register Files (PGRF) into VLIW to achieve a PGRF-VLIW architecture. For energy efficiency, we also propose an instruction scheduling algorithm called the Deadline-Constrained Clustered Scheduling (DCCS) algorithm. The algorithm clusters the data dependence graph to reduce data transfer energy and makes optimal use of low-powered local registers for tree-structured data dependence graphs. The results of evaluations conducted using the MiBench and DSPstone benchmark suites substantiate the expected power saving and scaling effects.
Statements, data types and intrinsic procedures in the Fortran standards (1966-2008)
Authors: Gorelik A. M.
Published: July 2014

This paper contains the tables of statements, data types and intrinsic procedures in consecutive Fortran standards: from Fortran 66 up to Fortran 2008.
Yagi Array of Microstrip Quarter-Wave Patch Antennas with Microstrip Lines Coupling
Authors: Liu Juhua , Kang Yue , Chen Jie , Long Yunliang
Published: July 2014

A new kind of Yagi array of quarter-wave patch antennas is presented. The Yagi array has a low profile, a wide bandwidth, and a high gain. A main beam close to endfire is produced, with a vertical polarization in the horizontal plane. A set of microstrip lines are introduced between the driven element and the first director element to enhance the coupling between them, and therefore the bandwidth could be increased and the back lobes could be suppressed. Measured results show that the Yagi array with 4 elements generates a peak gain of about 9.7 dBi, a front-to-back ratio higher than 10 dB, and a 10 dB return loss band from 4.68 GHz to 5.24 GHz, with a profile of 1.5 mm and an overall size of 80 × 100 mm2. An increase of the number of director elements would enhance the gain and have the main beam pointing closer to endfire.
Developing a Collaborative Planning Framework for Sustainable Transportation
Authors: Özener Okan Örsan
Published: July 2014

Currently, as being the highest petroleum consuming sector in the world, transportation significantly contributes to the total greenhouse gas emissions in the world. Road transportation not only is responsible for approximately 20% of the total emissions of carbon dioxide in the EU and in the US but also has a steadily increasing trend in contributing to global warming. Initiatives undertaken by authorities, such as Emission cap and trade in the EU, limit the emissions resulted from the actions of the companies and also give economic incentives to companies to reduce their emissions. However, in logistics systems with multiple entities, it is difficult to assess the responsibilities of the companies both in terms of costs and emissions. In this study, we consider a delivery network with multiple customers served by a single carrier, which executes a delivery plan with the minimum transportation cost, and allocate the resulting costs and the emissions among the customers in a fair manner. We develop allocation mechanisms for both costs and emissions. In order to develop a mechanism that provides further reduction of the emissions, we study a setting where the carrier takes the responsibility of the emissions and reflects the resulting inefficiencies while charging the customers.
Management of Intrathoracic Benign Schwannomas of the Brachial Plexus
Authors: Bandiera Alessandro , Negri Giampiero , Melloni Giulio , Mandelli Carlo , Gerevini Simonetta , Carretta Angelo , Ciriaco Paola , Puglisi Armando , Zannini Piero
Published: July 2014

Primary tumours of the brachial plexus are rare entities. They usually present as extrathoracic masses located in the supraclavicular region. This report describes two cases of benign schwannomas arising from the brachial plexus with an intrathoracic growth. In the first case the tumour was completely intrathoracic and it was hardly removed through a standard posterolateral thoracotomy. In the second case the tumour presented as a cervicomediastinal lesion and it was resected through a one-stage combined supraclavicular incision followed by left video-assisted thoracoscopic surgery. A brachial plexus tumour should be suspected not only in patients with a supraclavicular or cervicomediastinal mass but also in those with intrathoracic apical lesions. A preoperative magnetic resonance imaging study of brachial plexus should be performed in such cases in order to plan the correct surgical approach.
Study of Swelling Properties and Thermal Behavior of Poly(N,N-Dimethylacrylamide-co-Maleic Acid) Based Hydrogels
Authors: Bennour Sadjia , Louzri Fatma
Published: July 2014

Hydrogels copolymers N,N-dimethylacrylamide (DMA) and maleic acid (MA) were prepared by free-radical polymerization at 56°C in aqueous solution, using N,N-methylenebisacrylamide (NMBA) as cross-linking agent and potassium persulfate (KPS) as initiator. The effects of comonomer composition, cross-linker content, and variation of pH solutions on the swelling behavior of polymers were investigated. The obtained results showed an increase of the swelling of poly(N,N-dimethylacrylamide-co-maleic acid) (P(DMA-MAx)) as the content of maleic acid increases in the polymeric matrix, while they indicate a great reduction of the degree of swelling as the cross-linking agent ratio increases. It was also shown that the swelling of copolymer hydrogels increased with the increase of pH and the maximum extent was reached at pH 8.7 in all compositions. Fourier transform infrared spectroscopy (FTIR) revealed the existence of hydrogen bonding interactions between the carboxylic groups of MA and the carbonyl groups of DMA. Differential scanning calorimetry analysis (DSC) showed an increase of the glass-transition temperature (Tg) as concentrations of MA and NMBA increased. Thermogravimetric analysis (TGA) of copolymers was performed to investigate the degradation mechanism.
Neuroprotective Effects of Cuscutae Semen in a Mouse Model of Parkinson’s Disease
Authors: Ye Minsook , Lee Seul gi , Chung Eun Sook , Lim Su-jin , Kim Won Seob , Yoon Heera , Kim Sun Kwang , Ahn Kwang Sung , Jang Young Pyo , Bae Hyunsu
Published: July 2014

Parkinson’s disease (PD) is a neurodegenerative movement disorder that is characterized by the progressive degeneration of the dopaminergic (DA) pathway. 1‐Methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP) causes damage to the DA neurons, and 1‐4‐methyl‐4‐phenylpyridinium (MPP+) causes cell death in differentiated PC12 cells that is similar to the degeneration that occurs in PD. Moreover, MPTP treatment increases the activity of the brain’s immune cells, reactive oxygen species‐ (ROS‐) generating processes, and glutathione peroxidase. We recently reported that Cuscutae Semen (CS), a widely used traditional herbal medicine, increases cell viability in a yeast model of PD. In the present study, we examined the inhibitory effect of CS on the neurotoxicity of MPTP in mice and on the MPP+‐induced cell death in differentiated PC12 cells. The MPTP‐induced loss of nigral DA neurons was partly inhibited by CS‐mediated decreases in ROS generation. The activation of microglia was slightly inhibited by CS, although this effect did not reach statistical significance. Furthermore, CS may reduce the MPP+ toxicity in PC12 cells by suppressing glutathione peroxidase activation. These results suggest that CS may be beneficial for the treatment of neurodegenerative diseases such as PD.