Range Scan Registration Using Reduced Deformable Models

We present an unsupervised method for registering range scans of deforming, articulated shapes. The key idea is to model the motion of the underlying object using a reduced deformable model. We use a linear skinning model for its simplicity and represent the weight functions on a regular grid localized to the surface geometry. This decouples the deformation model from the surface representation and allows us to deal with the severe occlusion and missing data that is inherent in range scan data. We formulate the registration problem using an objective function that enforces close alignment of the 3D data and includes an intuitive notion of joints. This leads to an optimization problem that we solve using an efficient EM-type algorithm. With our algorithm we obtain smooth deformations that accurately register pairs of range scans with significant motion and occlusion. The main advantages of our approach are that it does not require user specified markers, a template, nor manual segmentation of the surface geometry into rigid parts.     

Reliable Location and Regression Estimates with Application to Range Image Segmentation

Range images provide important sources of information in many three-dimensional robot vision problems such as navigation and object recognition. Many physical factors, however, introduce noise to the discrete measurements in range images, identifying the need to reassess the error distribution in samples taken from real range images. This paper suggests the use of the L _p norms to yield reliable estimates of location and regression coefficients. This particular approach is compared against two commonly used approaches: Equally Weighted Least Squares, which minimizes the L₂ norm; and the Chebychev approximation, which minimizes the L ₁ norm. The problem is a weighted least squares case where the weights are derived from the chosen parameter, p, and its ability to yield a variety of location estimates spanning from the sample mean to the sample median. These two estimates have a wide application in image processing that includes noise removal. This paper will show the problems associated with these two techniques, and suggest experimental solutions to minimize them. A specific operating range is determined in which the L _p norms perform well and a regression module is used in conjunction with a region-growing segmentation algorithm to provide a reliable partition of range images.     

Terminating Renewal Processes: Analytical-Statistical Estimates and Their Efficiency

An approach is proposed to the construction of different unbiased analytical-statistical estimates for calculation of the termination time of different renewal processes by the Monte Carlo method. The processes are typical of queuing systems, reliability theory, and risk analysis of renewal processes and to the analysis of their efficiency using the algorithmic language Maple V.The results were obtained during two scientific visits to the STORM Research Center of the University of North London in 1998–1999 with a sponsor support from the Royal Society in Great Britain and within the framework of the project UKR-01-008.__________Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 138–155, January–February 2005.     

基于范围分割数据的负载平衡算法的研究*

基于范围分割提出了一个有效的、渐近的负载平衡算法,可确保在任意时间的存储平衡,理论分析证明了该方法的有效性。     

Order and Disorder in Product Innovation Models

This article argues that the conceptual development of product innovation models goes hand in hand with paradigmatic changes in the field of organization science. Remarkable similarities in the change of organizational perspectives and product innovation models are noticeable. To illustrate how changes in the organizational paradigm are being translated into changes in new product development (NPD) practices, five NPD models are presented: the sequential, compression, flexible, integrative and improvisational models. The evolution of product innovation management shows a move from planned and mechanistic, towards emergent and organic models. Such a process of re‐orientation poses several challenges that are presented in the form of six propositions: from universal to contingent models, from invariant to flexible practices, from avoiding risks to taking advantage of opportunities, from planning to learning, from exclusive teams to inclusive networks, from structure to structured chaos.     

On the Efficient Evaluation of Coalescence Integrals in Population Balance Models

The solution of population balance equations is a function f(t,r,x) describing a population density of particles of the property x at time t and space r. For instance, the additional independent variable x may denote the particle size. The describing partial differential equation contains additional sink and source terms involving integral operators. Since the coordinate x adds at least one further dimension to the spatial directions and time coordinate, an efficient numerical treatment of the integral terms is crucial. One of the more involved integral terms appearing in population balance models is the coalescence integral, which is of the form ∫ ₀ ^x κ(x–y, y) f(y) f(x–y)dy. In this paper, we describe an evaluation method of this integral which needs only operations, where n is the number of degrees of freedom with respect to the variable x. This cost can also be obtained in the case of a grid geometrically refined towards x=0.     

Stochastic Models and Adaptive Algorithms for Energy Balance in Sensor Networks

We consider the important problem of energy balanced data propagation in wireless sensor networks and we extend and generalize previous works by allowing adaptive energy assignment. We consider the data gathering problem where data are generated by the sensors and must be routed toward a unique sink. Sensors route data by either sending the data directly to the sink or in a multi-hop fashion by delivering the data to a neighbouring sensor. Direct and neighbouring transmissions require different levels of energy consumption. Basically, the protocols balance the energy consumption among the sensors by computing the adequate ratios of direct and neighbouring transmissions. An abstract model of energy dissipation as a random walk is proposed, along with rigorous performance analysis techniques. Two efficient distributed algorithms are presented and analyzed, by both rigorous means and simulation. The first one is easy to implement and fast to execute. The protocol assumes that sensors know a-priori the rate of data they generate. The sink collects and processes all these information in order to compute the relevant value of the protocol parameter. This value is transmitted to the sensors which individually compute their optimal ratios of direct and neighbouring transmissions. The second protocol avoids the necessary a-priori knowledge of the data rate generated by sensors by inferring the relevant information from the observation of the data paths. Furthermore, this algorithm is based on stochastic estimation methods and is adaptive to environmental changes.     

Using Term-Graph Rewriting Models to Analyse Relative Space Efficiency

Space leaks are a common operational problem in programming languages with automated memory man-agement. Graph rewriting is a natural model of operational behaviour. This paper summarises a PhD thesis which gives a graph-rewriting framework suitable for modelling language implementations and proof techniques for determining the presence or absence of leaks. The approach is to model implementations as graph evaluators with garbage collectors. An evaluator may leak relative to another evaluator, with respect to a translation between their states. Leaks are classified according to their cause and the behaviour which exposes them.Graphs naturally model state size, but we argue that this is too concrete. Accurate evaluators are introduced which allow for a more abstract model in which initial program size is ignored. Evaluators are compared by defining a translation between graphs. Space-safe translations, and non-standard garbage collectors, are defined as another kind of term-graph rewrite system. Leaky evaluators are detected by a proof method which searches for graphs whose evaluation trace is a self-feeding rule sequence.     

Models of Computation of a Multialternative Prediction Graph on the Basis of Analytical Estimates

Problems of the theory of construction and computation of prediction graphs are considered. Questions of solution of the problem of quantitative analysis of prediction graphs are investigated.__________Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 91–106, March–April 2005.     

网络游戏技术与产业效益开发模式探讨

我国网络游戏以每年40%以上的速度持续增长,同时网游以平均1：2.5倍左右的比例带动电信以及相关IT产业的增长。所以研究网游经济的绿色可持续发展模式是非常有必要的,而作为网游经济效益的核心网游技术显得尤为重要。     

Long Range Predictive Control of Nonlinear Processes Based on Recurrent Neuro-Fuzzy Network Models

A recurrent neuro-fuzzy network-based nonlinear long range model predictive control strategy is proposed in this paper. The process operation is partitioned into several fuzzy operating regions. Within each region, a local linear model is used to model the process. The global model output is obtained through the centre of gravity defuzzification. Based upon a neuro-fuzzy network model, a nonlinear model-based predictive controller can be developed by combining several local linear model-based predictive controllers which usually have analytical solutions. This strategy avoids the time consuming numerical optimisation procedure, and the uncertainty in convergence to the global optimum which are typically seen in conventional nonlinear model-based predictive control strategies. Furthermore, control actions obtained based on local incremental models contain integration actions which can nat-urally eliminate static control offsets. The technique is demonstrated by an application to the modelling and control of liquid level in a water tank.     

基于感知度模型的卫星侦察舰船目标效能评估研究

信息化作战条件下,卫星侦察舰船目标情报的获取成为分析判断现代战争海战场态势的重要依据。为评估卫星侦察监视效能,文章引入感知度概念,建立卫星侦察舰船目标感知度评估模型,给出模型定义及计算公式,深入分析了感知度评估模型的构建因素。针对舰船目标区域,通过引入网格空间,计算感知度,给出仿真评估流程和步骤。以我国领海某区域为例进行仿真分析,仿真结果表明模型能够较好的评估多颗卫星联合侦察效果。     

Simultaneous Registration of Multiple Range Views for Use in Reverse Engineering of CAD Models

When reverse engineering a CAD model, it is necessary to integrate information from several views of an object into a common reference frame. Given a rough initial alignment of local 3-D shape data in several images, further refinement is achieved using an improved version of the recently popular Iterative Closest Point algorithm. Improved data correspondence is determined by considering the merging data sets as a whole. A potentially incorrect distance threshold for removing outlier correspondences is not needed as in previous efforts. Incremental pose adjustments are computed simultaneously for all data sets, resulting in a more globally optimal set of transformations. Individual motion updates are computed using force-based optimization, by considering the data sets as implicitly connected by groups of springs. Experiments on both 2-D and 3-D data sets show that convergence is possible even for very rough initial positionings, and that the final registration accuracy typically approaches less than one quarter of the interpoint sampling resolution of the images.     

Role Models for Radical Innovations in Times of Open Innovation

In this paper, we study the influence of innovator roles in highly innovative ventures. In order to obtain a differentiated picture we take into account the degree of innovativeness as a moderating variable. To test our hypotheses we use a sample of 146 highly innovative new product development projects. We choose a rigorous sampling design and apply state‐of‐the‐art measures for the degree of innovativeness. Furthermore, we apply multi‐trait‐multi‐method methodology (MTMM) to enhance the validity of our study. The results show that innovator roles have a strong influence on innovation success but these influences are positively and negatively moderated by innovativeness. The moderating influences depend on the type of innovativeness. Remarkably, with increasing technological innovativeness innovator roles which create inter‐organizational links with the outside world appear to be more important than intra‐organizational linker roles, and support from high‐ranked organizational members turns out to have a significant negative effect on project success with higher degrees of technological innovativeness. Possible explanations for these findings are discussed and consequences for innovation research and innovation management are shown.     

On the Treatment of Repeated Observations in Panel Data: Efficiency of Mixed Logit Parameter Estimates

Travel demand models are usually estimated using cross-sectional data. Although the use of panel data has recently increased in many areas, there are still many aspects that have not been fully analyzed. Some examples of unexplored topics are: the optimal length of panel surveys and the resulting issue of how to model panel data correctly in the presence of repeated observations (for example, several trips per week, by people in a panel with waves every six months) and whether, and to which extent, this affects the efficiency of the estimated parameters and their capability to replicate the true situation. In this paper we analyse this issue and test the effect of including journeys made, with the same characteristics, several times in a week. A broad variety of models accounting for fixed parameters but also for random heterogeneity and correlation among individuals were estimated using real and synthetic data. The real data comes from the Santiago Panel (2006–2008), while the synthetic data were appropriately generated to examine the same problem in a controlled experiment. Our results show that having more observations per individual increases the probability of capturing more effects (i.e. different types of heterocedasticity), but having identical observations in a data panel reduces the capability to reproduce the true phenomenon. Consequently, the definition of panel survey length demands us to consider the implicit level of routine (i.e. the proportion of identical observations) in it.     

Estimates of ocean coherence time by an interferometric SAR

Abstract

The azimuthal resolution of the Synthetic Aperture Radar (SAR) when imaging the permanently moving ocean surface is determined by the coherence time of the imaged scene. The scene coherence time thus constitutes one of the major parameters in SAR imagery of the ocean. The present study shows how the direct estimate of this parameter under the actual experimental conditions can be performed using a two-antenna interferometric SAR. The present results arc in agreement with earlier estimates.     

Range image segmentation by an effective jump-diffusion method

This paper presents an effective jump-diffusion method for segmenting a range image and its associated reflectance image in the Bayesian framework. The algorithm works on complex real-world scenes (indoor and outdoor), which consist of an unknown number of objects (or surfaces) of various sizes and types, such as planes, conics, smooth surfaces, and cluttered objects (like trees and bushes). Formulated in the Bayesian framework, the posterior probability is distributed over a solution space with a countable number of subspaces of varying dimensions. The algorithm simulates Markov chains with both reversible jumps and stochastic diffusions to traverse the solution space. The reversible jumps realize the moves between subspaces of different dimensions, such as switching surface models and changing the number of objects. The stochastic Langevin equation realizes diffusions within each subspace. To achieve effective computation, the algorithm precomputes some importance proposal probabilities over multiple scales through Hough transforms, edge detection, and data clustering. The latter are used by the Markov chains for fast mixing. The algorithm is tested on 100 1D simulated data sets for performance analysis on both accuracy and speed. Then, the algorithm is applied to three data sets of range images under the same parameter setting. The results are satisfactory in comparison with manual segmentations.