Piecewise‐planar Reconstruction of Multi‐room Interiors with Arbitrary Wall Arrangements

Reconstructing the as‐built architectural shape of building interiors has emerged in recent years as an important and challenging research problem. An effective approach must be able to faithfully capture the architectural structures and separate permanent components from clutter (e.g. furniture), while at the same time dealing with defects in the input data. For many applications, higher‐level information on the environment is also required, in particular the shape of individual rooms. To solve this ill‐posed problem, state‐of‐the‐art methods assume constrained input environments with a 2.5D or, more restrictively, a Manhattan‐world structure, which significantly restricts their applicability in real‐world settings. We present a novel pipeline that allows to reconstruct general 3D interior architectures, significantly increasing the range of real‐world architectures that can be reconstructed and labeled by any interior reconstruction method to date. Our method finds candidate permanent components by reasoning on a graph‐based scene representation, then uses them to build a 3D linear cell complex that is partitioned into separate rooms through a multi‐label energy minimization formulation. We demonstrate the effectiveness of our method by applying it to a variety of real‐world and synthetic datasets and by comparing it to more specialized state‐of‐the‐art approaches.     

Transparent and Specular Object Reconstruction

This state of the art report covers reconstruction methods for transparent and specular objects or phenomena. While the 3D acquisition of opaque surfaces with Lambertian reflectance is a well‐studied problem, transparent, refractive, specular and potentially dynamic scenes pose challenging problems for acquisition systems. This report reviews and categorizes the literature in this field. Despite tremendous interest in object digitization, the acquisition of digital models of transparent or specular objects is far from being a solved problem. On the other hand, real‐world data is in high demand for applications such as object modelling, preservation of historic artefacts and as input to data‐driven modelling techniques. With this report we aim at providing a reference for and an introduction to the field of transparent and specular object reconstruction. We describe acquisition approaches for different classes of objects. Transparent objects/phenomena that do not change the straight ray geometry can be found foremost in natural phenomena. Refraction effects are usually small and can be considered negligible for these objects. Phenomena as diverse as fire, smoke, and interstellar nebulae can be modelled using a straight ray model of image formation. Refractive and specular surfaces on the other hand change the straight rays into usually piecewise linear ray paths, adding additional complexity to the reconstruction problem. Translucent objects exhibit significant sub‐surface scattering effects rendering traditional acquisition approaches unstable. Different classes of techniques have been developed to deal with these problems and good reconstruction results can be achieved with current state‐of‐the‐art techniques. However, the approaches are still specialized and targeted at very specific object classes. We classify the existing literature and hope to provide an entry point to this exiting field.     

软件体系结构质量评价概述

1.引言随着软件规模和复杂度的不断增大,对软件质量、成本、进度的要求越来越严格。软件质量是指软件对预期的一系列质量属性组合的满足程度。目前,人们已经普遍认识到软件质量控制在软件特别是大型软件开发过程中对开发效率、成本有重要的影响,甚至关系到开发最终是否成功。高质量的软件在维护和测试阶段的开销较低,复用的潜力大。因此,预测和控制软件质量的成熟技术成为迫切的需要。     

一种演化超图文法到状态转移系统的映射方法

运用模型检测技术验证动态演化的正确性,是近年来软件体系结构动态演化研究领域面临的一个挑战.然而,当前的方法很少考虑软件体系结构动态演化时的相关条件.针对该问题,提出用条件状态转移系统表示软件体系结构动态演化的状态模型,将软件体系结构超图映射为状态,演化规则运用映射为条件状态转移关系,给出软件体系结构动态演化的条件超图文法到条件状态转移系统的映射方法以及相应的实现算法,实现了软件体系结构动态演化的条件状态转移系统的构建,并证明了在该映射方法下,软件体系结构动态演化条件超图文法与条件状态转移系统的互模拟等价.最后通过案例分析,运用该方法以及模型检测技术,验证了软件体系结构动态演化的相关性质,从而验证了该方法的有效性.     

An overview of Dynamic Software Product Line architectures and techniques: Observations from research and industry

Over the last two decades, software product lines have been used successfully in industry for building families of systems of related products, maximizing reuse, and exploiting their variable and configurable options. In a changing world, modern software demands more and more adaptive features, many of them performed dynamically, and the requirements on the software architecture to support adaptation capabilities of systems are increasing in importance. Today, many embedded system families and application domains such as ecosystems, service-based applications, and self-adaptive systems demand runtime capabilities for flexible adaptation, reconfiguration, and post-deployment activities. However, as traditional software product line architectures fail to provide mechanisms for runtime adaptation and behavior of products, there is a shift toward designing more dynamic software architectures and building more adaptable software able to handle autonomous decision-making, according to varying conditions. Recent development approaches such as Dynamic Software Product Lines (DSPLs) attempt to face the challenges of the dynamic conditions of such systems but the state of these solution architectures is still immature. In order to provide a more comprehensive treatment of DSPL models and their solution architectures, in this research work we provide an overview of the state of the art and current techniques that, partially, attempt to face the many challenges of runtime variability mechanisms in the context of Dynamic Software Product Lines. We also provide an integrated view of the challenges and solutions that are necessary to support runtime variability mechanisms in DSPL models and software architectures.     

Exploiting Object Escape and Locking Information in Partial-Order Reductions for Concurrent Object-Oriented Programs

Explicit-state model checking tools often incorporate partial-order reductions to reduce the number of system states explored (and thus the time and memory required) for verification. As model checking techniques are scaled up to software systems, it is important to develop and assess partial-order reduction strategies that are effective for addressing the complex structures found in software and for reducing the tremendous cost of model checking software systems. In this paper, we consider a number of reduction strategies for model checking concurrent object-oriented software. We investigate a range of techniques that have been proposed in the literature, improve on those in several ways, and develop five novel reduction techniques that advance the state of the art in partial-order reduction for concurrent object-oriented systems. These reduction strategies are based on (a) detecting heap objects that are thread-local (i.e., can be accessed by a single thread) and (b) exploiting information about patterns of lock-acquisition and release in a program (building on previous work). We present empirical results that demonstrate upwards of a hundred fold reduction in both space and time over existing approaches to model checking concurrent Java programs. In addition to validating their effectiveness, we prove that the reductions preserve LTL_?X properties and describe an implementation architecture that allows them to be easily incorporated into existing explicit-state software model checkers.     

Interactive Ambiguity Resolution of Named Entities in Fictional Literature

Named entity recognition (NER) denotes the task to detect entities and their corresponding classes, such as person or location, in unstructured text data. For most applications, state of the art NER software is producing reasonable results. However, as a consequence of the methodological limitations and the well‐known pitfalls when analyzing natural language data, the NER results are likely to contain ambiguities. In this paper, we present an interactive NER ambiguity resolution technique, which enables users to create (post‐processing) rules for named entity recognition data based on the content and entity context of the analyzed documents. We specifically address the problem that in use‐cases where ambiguities are problematic, such as the attribution of fictional characters with traits, it is often unfeasible to train models on custom data to improve state of the art NER software. We derive an iterative process model for improving NER results, show an interactive NER ambiguity resolution prototype, illustrate our approach with contemporary literature, and discuss our work and future research.     

A formal approach to MpSoC performance verification

Multiprocessor system on chip designs use complex on-chip networks to integrate different programmable processor cores, specialized memories, and other components on a single chip. MpSoC have been become the architecture of choice in many industries. Their heterogeneity inevitably increases with intellectual-property integration and component specialization. System integration is becoming a major challenge in their design. Simulation is state of the art in MpSoC performance verification, but it has conceptual disadvantages that become disabling as complexity increases. Formal approaches offer a systematic alternative. The article presents a technology that uses event model interfaces and a novel event flow mechanism that extends formal analysis approaches from real-time system design into the multiprocessor system on chip domain.     

Integrated cognitive architectures: a survey

This article aims to present an account of the state of the art research in the field of integrated cognitive architectures by providing a review of six cognitive architectures, namely Soar, ACT-R, ICARUS, BDI, the subsumption architecture and CLARION. We conduct a detailed functional comparison by looking at a wide range of cognitive components, including perception, memory, goal representation, planning, problem solving, reasoning, learning, and relevance to neurobiology. In addition, we study the range of benchmarks and applications that these architectures have been applied to. Although no single cognitive architecture has provided a full solution with the level of human intelligence, important design principles have emerged, pointing to promising directions towards generic and scalable architectures with close analogy to human brains.     

JavAdaptor—Flexible runtime updates of Java applications

Software is changed frequently during its life cycle. New requirements come, and bugs must be fixed. To update an application, it usually must be stopped, patched, and restarted. This causes time periods of unavailability, which is always a problem for highly available applications. Even for the development of complex applications, restarts to test new program parts can be time consuming and annoying. Thus, we aim at dynamic software updates to update programs at runtime. There is a large body of research on dynamic software updates, but so far, existing approaches have shortcomings either in terms of flexibility or performance. In addition, some of them depend on specific runtime environments and dictate the program's architecture. We present JavAdaptor , the first runtime update approach based on Java that (a) offers flexible dynamic software updates, (b) is platform independent, (c) introduces only minimal performance overhead, and (d) does not dictate the program architecture. JavAdaptor combines schema changing class replacements by class renaming and caller updates with Java HotSwap using containers and proxies. It runs on top of all major standard Java virtual machines. We evaluate our approach's applicability and performance in non‐trivial case studies and compare it with existing dynamic software update approaches. Copyright © 2012 John Wiley & Sons, Ltd.     

Cooperative multi-robot belief space planning for autonomous navigation in unknown environments

We investigate the problem of cooperative multi-robot planning in unknown environments, which is important in numerous applications in robotics. The research community has been actively developing belief space planning approaches that account for the different sources of uncertainty within planning, recently also considering uncertainty in the environment observed by planning time. We further advance the state of the art by reasoning about future observations of environments that are unknown at planning time. The key idea is to incorporate within the belief indirect multi-robot constraints that correspond to these future observations. Such a formulation facilitates a framework for active collaborative state estimation while operating in unknown environments. In particular, it can be used to identify best robot actions or trajectories among given candidates generated by existing motion planning approaches, or to refine nominal trajectories into locally optimal paths using direct trajectory optimization techniques. We demonstrate our approach in a multi-robot autonomous navigation scenario and consider its applicability for autonomous navigation in unknown obstacle-free and obstacle-populated environments. Results indicate that modeling future multi-robot interaction within the belief allows to determine robot actions (paths) that yield significantly improved estimation accuracy.     

Comments on “What the Back of the Object Looks Like: 3D Reconstruction from Line Drawings without Hidden Lines”

I comment on a paper describing a method for deducing the hidden topology of an object portrayed in a 2D natural line drawing. The principal problem with this paper is that it cannot be considered an advance on (or even an equal of) the state of the art as the approach it describes makes the same limiting assumptions as approaches proposed 10 years ago. There are also important omissions in the review of related work.     

视觉跟踪技术综述

视觉跟踪问题是当前计算机视觉领域中的热点问题,本文对这一问题进行了详细的介绍.首先,对视觉跟踪技术在视频监视、图像压缩和三维重构等三个主要方面的应用进行了论述.其次,详细阐述了该技术的研究现状,介绍了其中的一些常用方法,为清楚说明这些方法,先对视觉跟踪问题进行了分类,然后介绍了处理视觉跟踪问题的两种思路即自底向上和自顶向下的思路,最后将具体的视觉跟踪方法分为四类进行了介绍,这四类分别是基于区域的跟踪、基于特征的跟踪、基于变形模板的跟踪和基于模型的跟踪.最后,从控制论角度给出视觉跟踪算法所面临的难点,即算法要满足鲁棒性、准确性和快速性要求时所遇到的困难,并对视觉跟踪问题的研究前景进行了展望.     

Extending applications using an advanced approach to DLL injection and API hooking

When programmers need to modify third‐party applications, they frequently do not have access to their source code. In such cases, DLL injection and API hooking are techniques that can be used to modify applications without intervening into their source code. The commonly used varieties of injection and hooking approaches have many practical limitations: they are inconvenient for a programmer to implement, do not work reliably in conjunction with all applications and with certain low‐level machine instructions. In this paper we present two novel approaches to DLL injection and API hooking, which we call Debugger‐aided DLL injection and Single Instruction Hooking. Our approaches overcome the limitations of the state‐of‐the art approaches. Despite incurring greater execution times, our approach allows extending of the applications in situations where the comparable approaches fail. As such, it has a notable practical value for beneficial practical applications of injection and hooking approaches, which are present in malware detection programs and computer security tools. Copyright © 2010 John Wiley & Sons, Ltd.     

Three‐dimensional reconstruction of underwater objects using wide‐aperture imaging SONAR

The estimation of the geometric structure of objects located underwater underpins a plethora of applications such as mapping shipwrecks for archaeology, monitoring the health of coral reefs, detecting faults in offshore oil rigs and pipelines, detection and identification of potential threats on the seabed, etc. Acoustic imaging is the most popular choice for underwater sensing. Underwater exploratory vehicles typically employ wide‐aperture Sound Navigation and Ranging (SONAR) imaging sensors. Although their wide aperture enables scouring large volumes of water ahead of them for obstacles, the resulting images produced are blurry due to integration over the aperture. Performing three‐dimensional (3D) reconstruction from this blurry data is notoriously difficult. This challenging inverse problem is further exacerbated by the presence of speckle noise and reverberations. The state‐of‐the‐art methods in 3D reconstruction from sonar either require bulky and expensive matrix‐arrays of sonar sensors or additional narrow‐aperture sensors. Due to its low footprint, the latter induces gaps between reconstructed scans. Avoiding such gaps requires slow and cumbersome scanning by the vehicles that carry the scanners. In this paper, we present two reconstruction methods enabling on‐site 3D reconstruction from imaging sonars of any aperture. The first of these presents an elegant linear formulation of the problem, as a blind deconvolution with a spatially varying kernel. The second method is a simple algorithmic approach for approximate reconstruction, using a nonlinear formulation. We demonstrate that our simple approximation algorithms perform 3D reconstruction directly from the data recorded by wide‐aperture systems, thus eliminating the need for multiple sensors to be mounted on underwater vehicles for this purpose. Additionally, we observe that the wide aperture may be exploited to improve the coverage of the reconstructed samples (on the scanned object's surface). We demonstrate the efficacy of our algorithms on simulated as well as real data acquired using two sensors, and we compare our work to the state of the art in sonar reconstruction. Finally, we show the employability of our reconstruction methods on field data gathered by an autonomous underwater vehicle.     

Formal verification of static software models in MDE: A systematic review

ContextModel-driven Engineering (MDE) promotes the utilization of models as primary artifacts in all software engineering activities. Therefore, mechanisms to ensure model correctness become crucial, specially when applying MDE to the development of software, where software is the result of a chain of (semi)automatic model transformations that refine initial abstract models to lower level ones from which the final code is eventually generated. Clearly, in this context, an error in the model/s is propagated to the code endangering the soundness of the resulting software. Formal verification of software models is a promising approach that advocates the employment of formal methods to achieve model correctness, and it has received a considerable amount of attention in the last few years.ObjectiveThe objective of this paper is to analyze the state of the art in the field of formal verification of models, restricting the analysis to those approaches applied over static software models complemented or not with constraints expressed in textual languages, typically the Object Constraint Language (OCL).MethodWe have conducted a Systematic Literature Review (SLR) of the published works in this field, describing their main characteristics.ResultsThe study is based on a set of 48 resources that have been grouped in 18 different approaches according to their affinity. For each of them we have analyzed, among other issues, the formalism used, the support given to OCL, the correctness properties addressed or the feedback yielded by the verification process.ConclusionsOne of the most important conclusions obtained is that current model verification approaches are strongly influenced by the support given to OCL. Another important finding is that in general, current verification tools present important flaws like the lack of integration into the model designer tool chain or the lack of efficiency when verifying large, real-life models.     

A review and future directions of SOA-based software architecture modeling approaches for System of Systems

Software architecture is a software system’s earliest set of design decisions that are critical for the quality of the system desired by the stakeholders. The architecture makes it easier to reason about and manage change during different phases of complex software life cycle. The modeling of software architecture for System of Systems (SoS) is a challenging task because of a system’s complexity arising from an integration of heterogeneous, distributed, managerially and operationally independent systems collaborating to achieve global missions. SoS is essentially dynamic and evolutionary by design requiring suitable architectural patterns to deal with runtime volatility. Service-oriented architecture offers several architectural features to these complex systems; these include, interoperability, loose coupling, abstraction and the provision of dynamic services based on standard interfaces and protocols. There is some research work available that provides critical analysis of current software architecture modeling approaches for SoS. However, none of them outlines the important characteristics of SoS or provides detailed analysis of current service-oriented architecture modeling approaches to model those characteristics. This article addresses this research gap and provides a taxonomy of software architecture modeling approaches, comparing and contrasting them using criteria critical for realization of SoS. Additionally, research gaps are identified, and future directions are outlined for building software architecture for SoS to model and reason about architecture quality in a more efficient way in service-oriented paradigm.     

A review of methods for automatic understanding of natural language mathematical problems

This article addresses the problem of understanding mathematics described in natural language. Research in this area dates back to early 1960s. Several systems have so far been proposed to involve machines to solve mathematical problems of various domains like algebra, geometry, physics, mechanics, etc. This correspondence provides a state of the art technical review of these systems and approaches proposed by different research groups. A unified architecture that has been used in most of these approaches is identified and differences among the systems are highlighted. Significant achievements of each method are pointed out. Major strengths and weaknesses of the approaches are also discussed. Finally, present efforts and future trends in this research area are presented.