Dynamic Insets for Context‐Aware Graph Navigation

Maintaining both overview and detail while navigating in graphs, such as road networks, airline route maps, or social networks, is difficult, especially when targets of interest are located far apart. We present a navigation technique called Dynamic Insets that provides context awareness for graph navigation. Dynamic insets utilize the topological structure of the network to draw a visual inset for off‐screen nodes that shows a portion of the surrounding area for links leaving the edge of the screen. We implement dynamic insets for general graph navigation as well as geographical maps. We also present results from a set of user studies that show that our technique is more efficient than most of the existing techniques for graph navigation in different networks.     

Context‐Based Coding of Adaptive Multiresolution Meshes

Multiresolution meshes provide an efficient and structured representation of geometric objects. To increase the mesh resolution only at vital parts of the object, adaptive refinement is widely used. We propose a lossless compression scheme for these adaptive structures that exploits the parent–child relationships inherent to the mesh hierarchy. We use the rules that correspond to the adaptive refinement scheme and store bits only where some freedom of choice is left, leading to compact codes that are free of redundancy. Moreover, we extend the coder to sequences of meshes with varying refinement. The connectivity compression ratio of our method exceeds that of state‐of‐the‐art coders by a factor of 2–7. For efficient compression of vertex positions we adapt popular wavelet‐based coding schemes to the adaptive triangular and quadrangular cases to demonstrate the compatibility with our method. Akin to state‐of‐the‐art coders, we use a zerotree to encode the resulting coefficients. Using improved context modelling we enhanced the zerotree compression, cutting the overall geometry data rate by 7% below those of the successful Progressive Geometry Compression. More importantly, by exploiting the existing refinement structure we achieve compression factors that are four times greater than those of coders which can handle irregular meshes.     

C‐LOD: Context‐aware Material Level‐of‐Detail applied to Mobile Graphics

Attention‐based Level‐Of–Detail (LOD) managers downgrade the quality of areas that are expected to go unnoticed by an observer to economize on computational resources. The perceptibility of lowered visual fidelity is determined by the accuracy of the attention model that assigns quality levels. Most previous attention based LOD managers do not take into account saliency provoked by context, failing to provide consistently accurate attention predictions. In this work, we extend a recent high level saliency model with four additional components yielding more accurate predictions: an object‐intrinsic factor accounting for canonical form of objects, an object‐context factor for contextual isolation of objects, a feature uniqueness term that accounts for the number of salient features in an image, and a temporal context that generates recurring fixations for objects inconsistent with the context. We conduct a perceptual experiment to acquire the weighting factors to initialize our model. We design C‐LOD, a LOD manager that maintains a constant frame rate on mobile devices by dynamically re‐adjusting material quality on secondary visual features of non‐attended objects. In a proof of concept study we establish that by incorporating C‐LOD, complex effects such as parallax occlusion mapping usually omitted in mobile devices can now be employed, without overloading GPU capability and, at the same time, conserving battery power.     

Quasi‐Time‐Dependent Controller for Discrete‐Time Switched Linear Systems With Mode‐Dependent Average Dwell‐Time

This paper is concerned with the stability and stabilization problem of a class of discrete‐time switched systems with mode‐dependent average dwell time (MDADT). A novel Lyapunov function, which is both mode‐dependent (MD) and quasi‐time‐dependent (QTD), is established. The new established Lyapunov function is allowed to increase at some certain time instants. A QTD controller is designed such that the system is globally uniformly asymptotically stable (GUAS) and has a guaranteed performance index. The new QTD robust controller designed in this paper is less conservative than the mode independent one which is frequently considered in literatures. Finally, a numerical example and a practical example are provided to illustrate the effectiveness of the developed results.      

SmartCanvas: Context‐inferred Interpretation of Sketches for Preparatory Design Studies

In early or preparatory design stages, an architect or designer sketches out rough ideas, not only about the object or structure being considered, but its relation to its spatial context. This is an iterative process, where the sketches are not only the primary means for testing and refining ideas, but also for communicating among a design team and to clients. Hence, sketching is the preferred media for artists and designers during the early stages of design, albeit with a major drawback: sketches are 2D and effects such as view perturbations or object movement are not supported, thereby inhibiting the design process. We present an interactive system that allows for the creation of a 3D abstraction of a designed space, built primarily by sketching in 2D within the context of an anchoring design or photograph. The system is progressive in the sense that the interpretations are refined as the user continues sketching. As a key technical enabler, we reformulate the sketch interpretation process as a selection optimization from a set of context‐generated canvas planes in order to retrieve a regular arrangement of planes. We demonstrate our system (available at http:/geometry.cs.ucl.ac.uk/projects/2016/smartcanvas/ ) with a wide range of sketches and design studies.     

A Data‐Driven Framework for Visual Crowd Analysis

We present a novel approach for analyzing the quality of multi‐agent crowd simulation algorithms. Our approach is data‐driven, taking as input a set of user‐defined metrics and reference training data, either synthetic or from video footage of real crowds. Given a simulation, we formulate the crowd analysis problem as an anomaly detection problem and exploit state‐of‐the‐art outlier detection algorithms to address it. To that end, we introduce a new framework for the visual analysis of crowd simulations. Our framework allows us to capture potentially erroneous behaviors on a per‐agent basis either by automatically detecting outliers based on individual evaluation metrics or by accounting for multiple evaluation criteria in a principled fashion using Principle Component Analysis and the notion of Pareto Optimality. We discuss optimizations necessary to allow real‐time performance on large datasets and demonstrate the applicability of our framework through the analysis of simulations created by several widely‐used methods, including a simulation from a commercial game.     

Packet‐Loss‐Dependent Stabilization of Model‐Based Networked Control Systems

In this paper, the stabilization problem and controller design of model‐based networked control systems (MB‐NCSs) with both arbitrary and Markovian packet dropouts are discussed via the switched system approach. Different from the common way of using the last successfully transmitted information, the approximate state produced by the explicit plant model is applied to deal with the packet loss problem in our method. Based on the Lyapunov functional methodology and inequality techniques, some sufficient stabilization conditions are derived and stabilizing state feedback controllers are constructed. Moreover, by using the cone complementary linearation (CCL) method, a non‐linear minimization problem subject to some linear matrix inequalities (LMIs) is provided here to help find a sub‐optimal solution. Numerical examples and accompanying simulations illustrate the effectiveness and validity of our techniques, and also evidence of improvements over the existing literature.     

Feature‐Driven Visual Analytics of Chaotic Parameter‐Dependent Movement

Analyzing movements in their spatial and temporal context is a complex task. We are additionally interested in understanding the movements’ dependency on parameters that govern the processes behind the movement. We propose a visual analytics approach combining analytic, visual, and interactive means to deal with the added complexity. The key idea is to perform an analytical extraction of features that capture distinct movement characteristics. Different parameter configurations and extracted features are then visualized in a compact fashion to facilitate an overview of the data. Interaction enables the user to access details about features, to compare features, and to relate features back to the original movement. We instantiate our approach with a repository of more than twenty accepted and novel features to help analysts in gaining insight into simulations of chaotic behavior of thousands of entities over thousands of data points. Domain experts applied our solution successfully to study dynamic groups in such movements in relation to thousands of parameter configurations.     

频域基于灰度共生矩阵的人群密度估计

人群密度估计对于大型公共设施的设计和人群的安全十分重要.本文提出了一种基于二维快速傅立叶变换和灰度共生矩阵的人群密度特征提取方法.主要思想是依据不同密度的人群图像在其频谱图上的不同,将频谱图视为纹理图像,利用纹理分析的方法提取能够表现这些不同的纹理特征.进而利用Adaboost实现人群密度级别的分类.实验结果表明本文提出的方法在具有不逊于其他算法的准确率的情况下,计算速度明显提高.     

Interaction‐Dependent Semantics for Illustrative Volume Rendering

In traditional illustration the choice of appropriate styles and rendering techniques is guided by the intention of the artist. For illustrative volume visualizations it is difficult to specify the mapping between the 3D data and the visual representation that preserves the intention of the user. The semantic layers concept establishes this mapping with a linguistic formulation of rules that directly map data features to rendering styles. With semantic layers fuzzy logic is used to evaluate the user defined illustration rules in a preprocessing step. In this paper we introduce interaction‐dependent rules that are evaluated for each frame and are therefore computationally more expensive. Enabling interaction‐dependent rules, however, allows the use of a new class of semantics, resulting in more expressive interactive illustrations. We show that the evaluation of the fuzzy logic can be done on the graphics hardware enabling the efficient use of interaction‐dependent semantics. Further we introduce the flat rendering mode and discuss how different rendering parameters are influenced by the rule base. Our approach provides high quality illustrative volume renderings at interactive frame rates, guided by the specification of illustration rules.     

A New Delay‐Dependent Stability Criterion For Neutral Delay‐Differential Systems

This paper investigates the problem of asymptotic stability for neutral delay‐differential systems. Using the Lyapunov method, we derive a new delay‐dependent sufficient condition for the stability of systems in terms of the linear matrix inequality (LMI). Numerical examples show that the results obtained in this paper significantly improve the estimate of stability limit over some existing results reported previously in the literature.     

An Analysis of the In‐Out BRDF Factorization for View‐Dependent Relighting

Interactive rendering with dynamic natural lighting and changing view is a long‐standing goal in computer graphics. Recently, precomputation‐based methods for all‐frequency relighting have made substantial progress in this direction. Many of the most successful algorithms are based on a factorization of the BRDF into incident and outgoing directions, enabling each term to be precomputed independent of viewing direction, and re‐combined at run‐time. However, there has so far been no theoretical understanding of the accuracy of this factorization, nor the number of terms needed. In this paper, we conduct a theoretical and empirical analysis of the BRDF in‐out factorization. For Phong BRDFs, we obtain analytic results, showing that the number of terms needed grows linearly with the Phong exponent, while the factors correspond closely to spherical harmonic basis functions. More generally, the number of terms is quadratic in the frequency content of the BRDF along the reflected or half‐angle direction. This analysis gives clear practical guidance on the number of factors needed for a given material. Different objects in a scene can each be represented with the correct number of terms needed for that particular BRDF, enabling both accuracy and interactivity.     

Quad‐Rotor Modeling and Attitude Control Using State‐Dependent ARX Type Model

A state‐dependent autoregressive with exogenous variables (SD‐ARX) model whose functional coefficients are approximated by sets of radial basis function (RBF) networks is proposed to describe the dynamic behavior of a quad‐rotor in this paper. This model is identified offline and used as an internal predictor of a receding horizon predictive controller to address the quad‐rotor's attitude control issue. In addition, the physical constraints of the system have been also taken into account during the controller design process. The results of real‐time control on a quad‐rotor aircraft illustrate satisfactory modeling accuracy in a large operating range and good performance of control approach proposed in this paper.     

Crowd sculpting: A space‐time sculpting method for populating virtual environments

We introduce “Crowd Sculpting”: a method to interactively design populated environments by using intuitive deformation gestures to drive both the spatial coverage and the temporal sequencing of a crowd motion. Our approach assembles large environments from sets of spatial elements which contain inter‐connectible, periodic crowd animations. Such a “Crowd Patches” approach allows us to avoid expensive and difficult‐to‐control simulations. It also overcomes the limitations of motion editing, that would result into animations delimited in space and time. Our novel methods allows the user to control the crowd patches layout in ways inspired by elastic shape sculpting: the user creates and tunes the desired populated environment through stretching, bending, cutting and merging gestures, applied either in space or time. Our examples demonstrate that our method allows the space‐time editing of very large populations and results into endless animation, while offering real‐time, intuitive control and maintaining animation quality.     

Crowd dynamics – being stuck

We consider a crowd of N persons trying to leave some area trough a small exit. The probability is calculated that an individual is able to withdraw from the crowd under one?s own steam. The problem is simulated within the generalized force model (D. Helbing, et al., Nature 407 (2000) 487), and all model parameters are taken from this paper. The results indicate, that in a crowd of 150 persons, this probability is not greater than ten percent. We also evaluate the number of helpers necessary to get the above probability of fifty percent.     

Reset Control Systems With Time‐Varying Delay: Delay‐Dependent Stability And Gain Performance Improvement

This paper considers the stability analysis of reset control systems with time‐varying delay. Based on sector reset conditions, delay‐dependent exponential stability and finite gain stability conditions are proposed, and piecewise Lyapunov functions are used such that less conservative results can be obtained, moreover, gain performance improvement results are presented to show the advantage of reset control. Numerical examples are given to show the effectiveness.     

Global Feature Tracking and Similarity Estimation in Time‐Dependent Scalar Fields

We present an algorithm for tracking regions in time‐dependent scalar fields that uses global knowledge from all time steps for determining the tracks. The regions are defined using merge trees, thereby representing a hierarchical segmentation of the data in each time step. The similarity of regions of two consecutive time steps is measured using their volumetric overlap and a histogram difference. The main ingredient of our method is a directed acyclic graph that records all relevant similarity information as follows: the regions of all time steps are the nodes of the graph, the edges represent possible short feature tracks between consecutive time steps, and the edge weights are given by the similarity of the connected regions. We compute a feature track as the global solution of a shortest path problem in the graph. We use these results to steer the – to the best of our knowledge – first algorithm for spatio‐temporal feature similarity estimation. Our algorithm works for 2D and 3D time‐dependent scalar fields. We compare our results to previous work, showcase its robustness to noise, and exemplify its utility using several real‐world data sets.     

Extracting Features from Time‐Dependent Vector Fields Using Internal Reference Frames

Extracting features from complex, time‐dependent flow fields remains a significant challenge despite substantial research efforts, especially because most flow features of interest are defined with respect to a given reference frame. Pathline‐based techniques, such as the FTLE field, are complex to implement and resource intensive, whereas scalar transforms, such as λ₂, often produce artifacts and require somewhat arbitrary thresholds. Both approaches aim to analyze the flow in a more suitable frame, yet neither technique explicitly constructs one. This paper introduces a new data‐driven technique to compute internal reference frames for large‐scale complex flows. More general than uniformly moving frames, these frames can transform unsteady fields, which otherwise require substantial processing of resources, into a sequence of individual snapshots that can be analyzed using the large body of steady‐flow analysis techniques. Our approach is simple, theoretically well‐founded, and uses an embarrassingly parallel algorithm for structured as well as unstructured data. Using several case studies from fluid flow and turbulent combustion, we demonstrate that internal frames are distinguished, result in temporally coherent structures, and can extract well‐known as well as notoriously elusive features one snapshot at a time.     

Robust Partially Mode Delay‐Dependent ℋ∞ Output Feedback Control of Discrete‐Time Networked Control Systems

In this paper, a methodology for designing an output feedback controller for discrete‐time networked control systems has been considered. More precisely, network‐induced delays between the sensor and the controller is modelled by a Markov chain with transition probabilities which are not assumed to be fully known. The systems parameter uncertainties are assumed to be norm‐bounded and possibly time‐varying. To the best of the authors knowledge, the problem of designing a partially mode delay‐dependent output feedback controller for NCSs with partially known transition probability matrix has not been investigated in the literature. Based on the Lyapunov‐Krasovskii functional approach, sufficient conditions for the existence of a robust partially mode delay‐dependent output feedback controller are given in terms of bilinear matrix inequalities which can be solved using a cone complementarity linearization algorithm. The proposed design methodology differs from the existing design methodologies in that dynamic output feedback controllers are parameterized by both modes and transition probabilities, as opposed to the existing design approaches which parameterize controllers by modes only. The results obtained reduce to the existing results on fully known transition matrices when transition probabilities are fully known. It is shown that the proposed methodology can be applied to real world systems. The proposed design methodology is verified by using a DC servo motor system where the plant and the controller are connected via a cellular network with partially known transition probability matrix.     

A Reset‐Time Dependent Approach for Stability Analysis of Nonlinear Reset Control Systems

A reset mechanism in controller can affect the stability property of a closed loop control system. In a simple word, there are stable reset control systems with unstable base‐systems and also unstable reset systems with stable base‐systems. The Lyapunov stability theory is a strong tool to investigate the stability of a nonlinear system. In this paper, based on the well‐known Lyapunov stability concept, some stability conditions for nonlinear reset control systems are addressed. These conditions are dependent on the reset‐times and hence the reset‐time intervals are explicitly emerged in the stability conditions. Some applications of these results are used in numerical examples to show the effectiveness of the proposed approach.