Exoskeleton: Curve network abstraction for 3D shapes

In this paper, we introduce the concept of an exoskeleton as a new abstraction of arbitrary shapes that succinctly conveys both the perceptual and the geometric structure of a 3D model. We extract exoskeletons via a principled framework that combines segmentation and shape approximation. Our method starts from a segmentation of the shape into perceptually relevant parts and then constructs the exoskeleton using a novel extension of the Variational Shape Approximation method. Benefits of the exoskeleton abstraction to graphics applications such as simplification and chartification are presented.     

Scalable nonlinear dynamical systems for agent steering and crowd simulation

We present a new methodology for agent modeling that is scalable and efficient. It is based on the integration of nonlinear dynamical systems and kinetic data structures. The method consists of three layers, which together model 3D agent steering, crowds and flocks among moving and static obstacles. The first layer, the local layer employs nonlinear dynamical systems theory to models low-level behaviors. It is fast and efficient, and it does not depend on the total number of agents in the environment. This dynamical systems-based approach also allows us to establish continuous numerical parameters for modifying each agent's behavior. The second layer, a global environment layer consists of a specifically designed kinetic data structure to track efficiently the immediate environment of each agent and know which obstacles/agents are near or visible to the given agent. This layer reduces the complexity in the local layer. In the third layer, a global planning layer, the problem of target tracking is generalized in a way that allows navigation in maze-like terrains, avoidance of local minima and cooperation between agents. We implement this layer based on two approaches that are suitable for different applications: One approach is to track the closest single moving or static target; the second is to use a pre-specified vector field, which may be generated automatically (with harmonic functions, for example) or based on user input to achieve the desired output. We also discuss how hybrid systems concepts for global planning can capitalize on both our layered approach and the continuous, reactive nature of our agent steering.

We demonstrate the power of the approach through a series of experiments simulating single/multiple agents and crowds moving towards moving/static targets in complex environments.     

Crowd simulation: applying mobile grids to the social force model

The social force model (SF) is able to reproduce many emergent phenomena observed in real crowds. Unfortunately, in some situations, such as low density environments, SF may produce counterintuitive results where the trajectories simulated look more like particles than to real people. We modify the SF model through the use of a mobile grid to allow the simulated pedestrians to change the direction of their desired velocity at reasonable times, thus avoiding nearby blocked or crowded areas smoothly. Our experiments focus on qualitative behavior, and verify that our model produces the desired trajectories of the pedestrians, achieving softer and more coherent trajectories when compared to the pure SF model solution. Like SF, our model reproduces the “faster-is-slower” and the arching underlying the clogging effects. Finally, we examine the occupation rates of the space when pedestrians were submitted to narrowed corridors and observe the “edge effect.”     

Making LibGuides Work: Student Interviews and Usability Tests

This article discusses student use of and feedback on LibGuides in an academic library. The authors conducted interviews and usability tests with on-campus and distance students to determine their preferences and expectations, as well as to identify specific pain points. Based on the findings, the authors changed LibGuides best practices at their institution and overhauled the LibGuides index page.     

Fracture Toughness of Dental Porcelains Evaluated by IF, SCF, and SEPB Methods

Fracture toughness of six dental porcelains with leucite content ranging from 0 to 22 vol% was evaluated by indentation fracture (IF), surface crack in flexure (SCF), and single edge pre-cracked beam (SEPB) methods. The results of the IF method were similar to those of the SCF method for all the porcelains investigated. The results of the SEPB were similar to those of the other two methods only for the glassy porcelains, but for leucite-based porcelains this method resulted in higher values of K _{I c} . Based on microstructure, fractographic analysis, and an additional single edge V-notched beam test, it was concluded that the pre-crack size influences the value of K _{I c} for porcelains reinforced by leucite. For design and failure analysis purposes, the K _{I c} determined by SCF method should be preferred, since fracture of dental restorations usually starts from small surface cracks.     

The Development Process of the Metropolitan Region of Sao Paulo: Contradictory and Accelerated-SP Brazil-Social and Environmental Aspects

This paper addresses the contradictions that can be seen within the process of economic and urban growth experienced by developing countries. Sao Paulo synthesizes these contradictions and is an example of how far people can go on environmental destruction when associated with social inequity.     

Facial movement analysis in ASL

In the age of speech and voice recognition technologies, sign language recognition is an essential part of ensuring equal access for deaf people. To date, sign language recognition research has mostly ignored facial expressions that arise as part of a natural sign language discourse, even though they carry important grammatical and prosodic information. One reason is that tracking the motion and dynamics of expressions in human faces from video is a hard task, especially with the high number of occlusions from the signers’ hands. This paper presents a 3D deformable model tracking system to address this problem, and applies it to sequences of native signers, taken from the National Center of Sign Language and Gesture Resources (NCSLGR), with a special emphasis on outlier rejection methods to handle occlusions. The experiments conducted in this paper validate the output of the face tracker against expert human annotations of the NCSLGR corpus, demonstrate the promise of the proposed face tracking framework for sign language data, and reveal that the tracking framework picks up properties that ideally complement human annotations for linguistic research.

---

Light scattering in polycrystalline alumina with bi-dimensionally large surface grains

Alumina ceramics with high in-line transmittance at 0.5–1.0 mm-thickness were prepared with different doping additives by sintering at 1850 °C in vacuum for 1–8 h. Depending on the additive contents and sintering variables bi-dimensionally large surface grains, caused by surface evaporation of MgO, had grown parallel to the surface with ～100 μm thickness and lateral sizes up to the millimeter range. The abnormal grain-growth process also resulted in the formation of pores entrapped inside the large surface grains within a narrow zone at 10–20 μm distance from the surface. The fraction of these pores is thickness-invariant. Scattering factors associated to the pores entrapped inside the bi-dimensionally large surface grains, second-phase particles, grain-boundaries, and microstructural surface defects are derived from the results of in-line transmission (at 600 nm) and are used together with microstructural characteristics to explain the light transmittance in these materials.     

Statistical cue integration in DAG deformable models

Deformable models are a useful modeling paradigm in computer vision. A deformable model is a curve, a surface, or a volume, whose shape, position, and orientation are controlled through a set of parameters. They can represent manufactured objects, human faces and skeletons, and even bodies of fluid. With low-level computer vision and image processing techniques, such as optical flow, we extract relevant information from images. Then, we use this information to change the parameters of the model iteratively until we find a good approximation of the object in the images. When we have multiple computer vision algorithms providing distinct sources of information (cues), we have to deal with the difficult problem of combining these, sometimes conflicting contributions in a sensible way. In this paper, we introduce the use of a directed acyclic graph (DAG) to describe the position and Jacobian of each point of deformable models. This representation is dynamic, flexible, and allows computational optimizations that would be difficult to do otherwise. We then describe a new method for statistical cue integration method for tracking deformable models that scales well with the dimension of the parameter space. We use affine forms and affine arithmetic to represent and propagate the cues and their regions of confidence. We show that we can apply the Lindeberg theorem to approximate each cue with a Gaussian distribution, and can use a maximum-likelihood estimator to integrate them. Finally, we demonstrate the technique at work in a 3D deformable face tracking system on monocular image sequences with thousands of frames.     

Exploring heuristic and optimum branching algorithms for image phylogeny

Currently, multimedia objects can be easily created, stored, (re)-transmitted, and edited for good or bad. In this sense, there has been an increasing interest in finding the structure of temporal evolution within a set of documents and how documents are related to one another overtime. This process, also known in the literature as Multimedia Phylogeny, aims at finding the phylogeny tree(s) that best explains the creation process of a set of near-duplicate documents (e.g., images/videos) and their ancestry relationships. Solutions to this problem have direct applications in forensics, security, copyright enforcement, news tracking services and other areas. In this paper, we explore one heuristic and one optimum branching algorithm for reconstructing the evolutionary tree associated with a set of image documents. This can be useful for aiding experts to track the source of child pornography image broadcasting or the chain of image distribution in time, for instance. We compare the algorithms with the state-of-the-art solution considering 350,000 test cases and discuss advantages and disadvantages of each one in a real scenario.