5971410
Time-space consistency in large-scale distributed virtual environments
Maintaining a consistent view of the simulated world among different simulation nodes is a fundamental problem in large-scale distributed virtual environments (DVEs). In this paper, we characterize this problem by quantifying the time-space inconsistency in a DVE. To this end, a metric is defined to measure the time-space inconsistency in a DVE. One major advantage of the metric is that it may be estimated based on some characteristic parameters of a DVE, such as clock asynchrony, message transmission delay, the accuracy of the dead reckoning algorithm, the kinetics of the moving entity, and human factors. Thus the metric can be used to evaluate the time-space consistency property of a DVE without the actual execution of the DVE application, which is especially useful in the design stage of a DVE. Our work also clearly shows how the characteristic parameters of a DVE are interrelated in deciding the time-space inconsistency, so that we may fine-tune the DVE to make it as consistent as possible. To verify the effectiveness of the metric, a Ping-Pong game is developed. Experimental results show that the metric is effective in evaluating the time-space consistency property of the game.
13349007
Greedy Algorithms for Client Assignment in Large-Scale Distributed Virtual Environments
Distributed Virtual Environments (DVEs), such as online games, military simulations, collaborative design, etc., are very popular nowadays. To support large-scale DVEs, a multi-server architecture is usually employed, and the virtual world is partitioned into multiple zones for load distribution. The client assignment problem arises when assigning the participating clients to the servers. Current approaches usually assign clients to servers according to the locations of clients in the virtual world, i.e., clients interacting in the same zone of the virtual world will be assigned to the same server. This approach may degrade the interactivity of DVEs if the network delay from a client to its assigned server is large. In this paper, we formulate the client assignment problem, and propose two algorithms to assign clients to servers in a more efficient way. The proposed algorithms are based on the heuristics developed for the well-known Terminal Assignment problem. Simulation results with the BRITE Internet Topology Generator show that our algorithms are effective in enhancing the interactivity of DVEs.
12104793
Planning for code buffer management in distributed virtual execution environments
Virtual execution environments have become increasingly useful in system implementation, with dynamic translation techniques being an important component for performance-critical systems. Many devices have exceptionally tight performance and memory constraints (e.g., smart cards and sensors in distributed systems), which require effective resource management. One approach to manage code memory is to download code partitions on-demand from a server and to cache the partitions in the resource-constrained device (client). However, due to the high cost of downloading code and re-translation, it is critical to intelligently manage the code buffer to minimize the overhead of code buffer misses. Yet, intelligent buffer management on the tightly constrained client can be too expensive. In this paper, we propose to move code buffer management to the server, where sophisticated schemes can be employed. We describe two schemes that use profiling information to direct the client in caching code partitions. One scheme is designed for workloads with stable run-time behavior, while the other scheme adapts its decisions for workloads with unstable behaviors. We evaluate and compare our schemes and show they perform well, compared to other approaches, with the adaptive scheme having the best performance overall.
12190727
Appearance Characterization of Linear Lambertian Objects, Generalized Photometric Stereo, and Illumination-Invariant Face Recognition
Traditional photometric stereo algorithms employ a Lambertian reflectance model with a varying albedo field and involve the appearance of only one object. In this paper, we generalize photometric stereo algorithms to handle all appearances of all objects in a class, in particular the human face class, by making use of the linear Lambertian property. A linear Lambertian object is one which is linearly spanned by a set of basis objects and has a Lambertian surface. The linear property leads to a rank constraint and, consequently, a factorization of an observation matrix that consists of exemplar images of different objects (e.g., faces of different subjects) under different, unknown illuminations. Integrability and symmetry constraints are used to fully recover the subspace bases using a novel linearized algorithm that takes the varying albedo field into account. The effectiveness of the linear Lambertian property is further investigated by using it for the problem of illumination-invariant face recognition using just one image. Attached shadows are incorporated in the model by a careful treatment of the inherent nonlinearity in Lambert's law. This enables us to extend our algorithm to perform face recognition in the presence of multiple illumination sources. Experimental results using standard data sets are presented
8505547
Face recognition from video: a CONDENSATION approach
The aim of this work is to investigate how to exploit the temporal information in a video sequence for the task of face recognition. Following the approach in (Li and Chellappa, 2000), we propose a probabilistic model parameterized by a tracking state vector and a recognizing identity variable, simultaneously characterizing the kinematics and identity of humans. We then invoke a CONDENSATION (Isard and Blake, 1996) approach to provide a numerical solution to the model. Once the joint posterior distribution of the state vector and the identity variable is estimated, we marginalize it over the state vector to yield a robust estimate of the posterior distribution of the identity variable. Due to the propagation of identity and dynamics, a degeneracy in the posterior distribution of the identity variable is achieved to give improved recognition. This evolving behavior is characterized using changes in entropy. The effectiveness of this approach is illustrated using experimental results on low-resolution video data.
1717304
Shape Regression Machine
We present a machine learning approach called shape regression machine (SRM) to segmenting in real time an anatomic structure that manifests a deformable shape in a medical image. Traditional shape segmentation methods rely on various assumptions. For instance, the deformable model assumes that edge defines the shape; the Mumford-Shah variational method assumes that the regions inside/outside the (closed) contour are homogenous in intensity; and the active appearance model assumes that shape/appearance variations are linear. In addition, they all need a good initialization. In contrast, SRM poses no such restrictions. It is a two-stage approach that leverages (a) the underlying medical context that defines the anatomic structure and (b) an annotated database that exemplifies the shape and appearance variations of the anatomy. In the first stage, it solves the initialization problem as object detection and derives a regression solution that needs just one scan in principle. In the second stage, it learns a nonlinear regressor that predicts the nonrigid shape from image appearance. We also propose a boosting regression approach that supports real time segmentation. We demonstrate the effectiveness of SRM using experiments on segmenting the left ventricle endocardium from an echocardiogram of an apical four chamber view.
14910614
An inequality between the diameter and the inverse dual degree of a tree
Let T be a nontrivial tree with diameter D(T) and radius R(T). Let I(T) be the inverse dual degree of T which is defined to be ΣueV(T) 1/d(u), where d(u) = (Συ∈ N(u)d(υ))/d(u) for u ∈ V(T). For any longest path P of T, denote by a(P) the number of vertices outside P with degree at least 2, b(P) the number of vertices on P with degree at least 3 and distance at least 2 to each of the end-vertices of P, and c(P) the number of vertices adjacent to one of the end-vertices of P and with degree at least 3. In this note we prove that I(T) ≥ D(T)/2+ a(P)/3 + b(P)/10 + c(P)/12 + 5/6. As a corollary we then get {R(T) + 1/3 if D(T) is odd, I(T) ≥ {R(T) + 5/6 if D(T) is even, with equality if and only if T is a path of at least four vertices. The latter inequality strengthens a conjecture made by the program Graffiti.