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22
Mobiscopes for human spaces
 IEEE Pervasive Computing
, 2007
"... The proliferation of affordable mobile devices with processing and sensing capabilities, together with the rapid growth in ubiquitous network connectivity, herald an era of Mobiscopes; networked sensing applications that rely on multiple mobile sensors to accomplish global tasks. These distributed s ..."
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Cited by 80 (10 self)
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The proliferation of affordable mobile devices with processing and sensing capabilities, together with the rapid growth in ubiquitous network connectivity, herald an era of Mobiscopes; networked sensing applications that rely on multiple mobile sensors to accomplish global tasks. These distributed sensing systems extend the model of traditional sensor networks, introducing challenges in data management, data integrity, privacy, and network system design. While several applications that fit the above description exist in prior literature, they provide tailored onetime solutions to what essentially is the same set of problems. It is time to work towards a general architecture that identifies common challenges and provides a generalizable methodology for the design of future Mobiscopes. Towards that end, this paper surveys a variety of current and emerging mobile, networked, sensing applications; articulates their common challenges; and provides architectural guidelines and design directions for this important
Subspace SelfCollision Culling
"... We show how to greatly accelerate selfcollision detection (SCD) for reduced deformable models. Given a triangle mesh and a set of deformation modes, our method precomputes Subspace SelfCollision Culling (SSCC) certificates which, if satisfied, prove the absence of selfcollisions for large parts o ..."
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Cited by 12 (1 self)
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We show how to greatly accelerate selfcollision detection (SCD) for reduced deformable models. Given a triangle mesh and a set of deformation modes, our method precomputes Subspace SelfCollision Culling (SSCC) certificates which, if satisfied, prove the absence of selfcollisions for large parts of the model. At runtime, bounding volume hierarchies augmented with our certificates can aggressively cull overlap tests and reduce hierarchy updates. Our method supports both discrete and continuous SCD, can handle complex geometry, and makes no assumptions about geometric smoothness or normal bounds. It is particularly effective for simulations with modest subspace deformations, where it can often verify the absence of selfcollisions in constant time. Our certificates enable low amortized costs, in time and across many objects in multibody dynamics simulations. Finally, SSCC is effective enough to support selfcollision tests at audio rates, which we demonstrate by producing the first sound simulations of clattering objects.
Approximation Algorithm for the Kinetic Robust KCenter Problem
, 2009
"... Two complications frequently arise in realworld applications, motion and the contamination of data by outliers. We consider a fundamental clustering problem, the kcenter problem, within the context of these two issues. We are given a finite point set S of size n and an integer k. In the standard k ..."
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Cited by 6 (3 self)
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Two complications frequently arise in realworld applications, motion and the contamination of data by outliers. We consider a fundamental clustering problem, the kcenter problem, within the context of these two issues. We are given a finite point set S of size n and an integer k. In the standard kcenter problem, the objective is to compute a set of k center points to minimize the maximum distance from any point of S to its closest center, or equivalently, the smallest radius such that S can be covered by k disks of this radius. In the discrete kcenter problem the disk centers are drawn from the points of S, and in the absolute kcenter problem the disk centers are unrestricted. We generalize this problem in two ways. First, we assume that points are in continuous motion, and the objective is to maintain a solution over time. Second, we assume that some given robustness parameter 0 < t ≤ 1 is given, and the objective is to compute the smallest radius such that there exist k disks of this radius that cover at least ⌈tn ⌉ points of S. We present a kinetic data structure (in the KDS framework) that maintains a (3 + ε)approximation for the robust discrete kcenter problem and a (4 + ε)approximation for the robust absolute kcenter problem, both under the assumption that k is a constant. We also improve on a previous 8approximation for the nonrobust discrete kinetic kcenter problem, for arbitrary k, and show that our data structure achieves a (4 + ε)approximation. All these results hold in any metric space of constant doubling dimension, which includes Euclidean space of constant dimension.
Maintaining Nets and Net Trees under Incremental Motion ⋆
"... Abstract. The problem of maintaining geometric structures for points in motion has been well studied over the years. Much theoretical work to date has been based on the assumption that point motion is continuous and predictable, but in practice, motion is typically presented incrementally in discret ..."
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Abstract. The problem of maintaining geometric structures for points in motion has been well studied over the years. Much theoretical work to date has been based on the assumption that point motion is continuous and predictable, but in practice, motion is typically presented incrementally in discrete time steps and may not be predictable. We consider the problem of maintaining a data structure for a set of points undergoing such incremental motion. We present a simple online model in which two agents cooperate to maintain the structure. One defines the data structure and provides a collection of certificates, which guarantee the structure’s correctness. The other checks that the motion over time satisfies these certificates and notifies the first agent of any violations. We present efficient online algorithms for maintaining both nets and net trees for a point set undergoing incremental motion in a space of constant dimension. We analyze our algorithms ’ efficiencies by bounding their competitive ratios relative to an optimal algorithm. We prove a constant factor competitive ratio for maintaining a slack form of nets, and our competitive ratio for net trees is proportional to the square of the tree’s height. 1
Compressing kinetic data from sensor networks
, 2009
"... We introduce a framework for storing and processing kinetic data observed by sensor networks. These sensor networks generate vast quantities of data, which motivates a significant need for data compression. We are given a set of sensors, each of which continuously monitors some region of space. We ..."
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Cited by 4 (3 self)
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We introduce a framework for storing and processing kinetic data observed by sensor networks. These sensor networks generate vast quantities of data, which motivates a significant need for data compression. We are given a set of sensors, each of which continuously monitors some region of space. We are interested in the kinetic data generated by a finite set of objects moving through space, as observed by these sensors. Our model relies purely on sensor observations; it allows points to move freely and requires no advance notification of motion plans. Sensor outputs are represented as random processes, where nearby sensors may be statistically dependent. We model the local nature of sensor networks by assuming that two sensor outputs are statistically dependent only if the two sensors are among the k nearest neighbors of each other. We present an algorithm for the lossless compression of the data produced by the network. We show that, under the statistical dependence and locality assumptions of our framework, asymptotically this compression algorithm encodes the data to within a constant factor of the informationtheoretic lower bound optimum dictated by the joint entropy of the system.
Maintaining Approximate Minimum Steiner Tree and kcenter for Mobile Agents in a Sensor Network
"... Abstract—We study the problem of maintaining group communication between m mobile agents, tracked and helped by n static networked sensors. We develop algorithms to maintain a O(lg n)approximation to the minimum Steiner tree of the mobile agents such that the maintenance message cost is on average ..."
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Abstract—We study the problem of maintaining group communication between m mobile agents, tracked and helped by n static networked sensors. We develop algorithms to maintain a O(lg n)approximation to the minimum Steiner tree of the mobile agents such that the maintenance message cost is on average O(lg n) per each hop an agent moves. The key idea is to extract a ‘hierarchical wellseparated tree (HST) ’ on the sensor nodes such that the tree distance approximates the sensor network hop distance by a factor of O(lg n). We then prove that maintaining the subtree of the mobile agents on the HST uses logarithmic messages per hop movement. With the HST we can also maintain O(lg n) approximate kcenter for the mobile agents with the same message cost. Both the minimum Steiner tree and the kcenter problems are NPhard and our algorithms are the first efficient algorithms for maintaining approximate solutions in a distributed setting. I.
Kinetic convex hulls and delaunay triangulations in the blackbox model
 In Proc. 27th Annu. Sympos. Comput. Geom
, 2011
"... Over the past decade, the kineticdatastructures framework has become the standard in computational geometry for dealing with moving objects. A fundamental assumption underlying the framework is that the motions of the objects are known in advance. This assumption severely limits the applicability ..."
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Over the past decade, the kineticdatastructures framework has become the standard in computational geometry for dealing with moving objects. A fundamental assumption underlying the framework is that the motions of the objects are known in advance. This assumption severely limits the applicability of KDSs. We study KDSs in the blackbox model, which is a hybrid of the KDS model and the traditional timeslicing approach. In this more practical model we receive the position of each object at regular time steps and we have an upper bound on dmax, the maximum displacement of any point in one time step. We study the maintenance of the convex hull and the Delaunay triangulation of a planar point set P in the blackbox model, under the following assumption on dmax: there is some constant k such that for any point p ∈ P the disk of radius dmax contains at most k points. We analyze our algorithms in terms of ∆k, the socalled kspread of P. We show how to update the convex hull at each time step in O(k∆k log 2 n) amortized time. For the Delaunay triangulation our main contribution is an analysis of the standard edgeflipping approach; we show that the number of flips is O(k2∆2k) at each time step.
Energybased SelfCollision Culling for Arbitrary Mesh Deformations
"... Figure 1: A squishy ball with 820 tentacles and over 1 million triangles, squishes and bounces on the ground, inducing numerous small interpenetrations. Our Energybased SelfCollision Culling (ESCC) method accelerates selfcollision detection (SCD) for arbitrarily deforming triangle meshes, such as ..."
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Cited by 2 (0 self)
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Figure 1: A squishy ball with 820 tentacles and over 1 million triangles, squishes and bounces on the ground, inducing numerous small interpenetrations. Our Energybased SelfCollision Culling (ESCC) method accelerates selfcollision detection (SCD) for arbitrarily deforming triangle meshes, such as this mesh animated using Oriented Particles [Müller and Chentanez 2011]. We observe an 11.5 × speedup over an optimized AABBTree SCD implementation on this challenging example. In this paper, we accelerate selfcollision detection (SCD) for a deforming triangle mesh by exploiting the idea that a mesh cannot self collide unless it deforms enough. Unlike prior work on subspace selfcollision culling which is restricted to lowrank deformation subspaces, our energybased approach supports arbitrary mesh deformations while still being fast. Given a bounding volume hierarchy (BVH) for a triangle mesh, we precompute Energybased SelfCollision Culling (ESCC) certificates on boundingvolumerelated submeshes which indicate the amount of deformation energy required for it to self collide. After updating energy values at runtime, many boundingvolume selfcollision queries can be culled using the ESCC certificates. We propose an affineframe Laplacianbased energy definition which sports a highly optimized certificate preprocess, and fast runtime energy evaluation. The latter is performed hierarchically to amortize Laplacian energy and affineframe estimation computations. ESCC supports both discrete and continuous SCD with detailed and nonsmooth geometry. We observe significant culling on many examples, with SCD speedups up to 26×. Links: DL PDF WEB 1
A New Approach to OutputSensitive Voronoi Diagrams
"... We describe a new algorithm for computing the Voronoi diagram of a set of n points in constantdimensional Euclidean space. The running time of our algorithm is O(f log n log ∆) where f is the output complexity of the Voronoi diagram and ∆ is the spread of the input, the ratio of largest to smallest ..."
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We describe a new algorithm for computing the Voronoi diagram of a set of n points in constantdimensional Euclidean space. The running time of our algorithm is O(f log n log ∆) where f is the output complexity of the Voronoi diagram and ∆ is the spread of the input, the ratio of largest to smallest pairwise distances. Despite the simplicity of the algorithm and its analysis, it improves on the state of the art for all inputs with polynomial spread and nearlinear output size. The key idea is to first build the Voronoi diagram of a superset of the input points using ideas from Voronoi refinement mesh generation. Then, the extra points are removed in a straightforward way that allows the total work to be bounded in terms of the output complexity, yielding the output sensitive bound. The removal only involves local flips and is inspired by kinetic data structures. 1
SIMULATING YARNBASED CLOTH
, 2011
"... Cloth is an important material to model and simulate correctly, both in computer graphics and other industrial applications. The commonly used models for cloth in computer graphics typically approximate the cloth as an elastic sheet with linear isotropic behavior inspired by the construction of wove ..."
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Cloth is an important material to model and simulate correctly, both in computer graphics and other industrial applications. The commonly used models for cloth in computer graphics typically approximate the cloth as an elastic sheet with linear isotropic behavior inspired by the construction of woven fabrics. However, they do a poor job of predicting the behavior of knits, which are driven by the complex interactions of yarn loops pulled through each other. This thesis presents a yarnbased model for cloth where yarns in the fabric are explicitly modeled as inextensible but flexible spline curves. Yarn dynamics are dictated by both energy terms and hard constraints, while friction interactions, a critical component of correct yarn behavior, are approximated using a velocity filter that penalizes locally nonrigid motion. Qualitative comparison of the model to observed deformations of handknitted samples in the laboratory showed that the model predicts key mechanical properties of different knits. Since this model is slower than sheetbased approaches, further work looked at accelerating the model through both localized rigidification and adaptive contact