Securing dynamic itineraries for mobile agent applications

In this paper we present a novel mechanism for the protection of dynamic itineraries for mobile agent applications. Itineraries that are decided as the agent goes are essential in complex applications based on mobile agents, but no approach has been presented until now to protect them. We have conceived a cryptographic scheme for shielding dynamic itineraries from tampering, impersonation and disclosure. By using trust strategically, our scheme provides a balanced trade-off between flexibility and security. Our protection scheme has been thought always bearing in mind a feasible implementation, and thus facilitates the development of applications that make use of it. An example application based on a real healthcare scenario is also presented to show its operation.     

SelfMotion: A declarative approach for adaptive service-oriented mobile applications

Modern society increasingly relies on mobile devices. This explains the growing demand for high quality software for such devices. To improve the efficiency of the development life-cycle, shortening time-to-market while keeping quality under control, mobile applications are typically developed by composing together ad-hoc developed components, services available on-line, and other third-party mobile applications. Applications are thus built as heterogeneous compositions, whose characteristics strongly depend on the components and services they integrate. To cope with unpredictable changes and failures, but also with the various settings offered by the plethora of available devices, mobile applications need to be as adaptive as possible. However, mainstream adaptation strategies are usually defined imperatively and require complex control strategies strongly intertwined with the application logic, yielding to applications that are difficult to build, maintain, and evolve. We address this issue by proposing a declarative approach to compose adaptive heterogeneous mobile applications. The advantages of this approach are demonstrated through an example inspired by an existing worldwide distributed mobile application, while the implementation of the proposed solution has been validated through a set of simulations and experiments aimed at illustrating its performance.     

Feature grouping and local soft match for mobile visual search

More powerful mobile devices stimulate mobile visual search to become a popular and unique image retrieval application. A number of challenges come up with such application, resulting from appearance variations in mobile images. Performance of state-of-the-art image retrieval systems is improved using bag-of-words approaches. However, for visual search by mobile images with large variations, there are at least two critical issues unsolved: (1) the loss of features discriminative power due to quantization; and (2) the underuse of spatial relationships among visual words. To address both issues, this paper presents a novel visual search method based on feature grouping and local soft match, which considers properties of mobile images and couples visual and spatial information consistently. First features of the query image are grouped using both matched visual features and their spatial relationships; and then grouped features are softly matched to alleviate quantization loss. An efficient score scheme is devised to utilize inverted file index and compared with vocabulary-guided pyramid kernels. Finally experiments on Stanford mobile visual search database and a collected database with more than one million images show that the proposed method achieves promising improvement over the approach with a vocabulary tree, especially when large variations exist in query images.     

在线复合模板模型表示的视觉目标跟踪

目的 视觉目标跟踪中,目标往往受到自身或场景中各种复杂干扰因素的影响,这对正确捕捉所感兴趣的目标信息带来极大的挑战。特别是,跟踪器所用的模板数据主要是在线学习获得,数据的可靠性直接影响到候选样本外观模型表示的精度。针对视觉目标跟踪中目标模板学习和候选样本外观模型表示等问题,采用一种较为有效的模板组织策略以及更为精确的模型表示技术,提出一种新颖的视觉目标跟踪算法。方法 跟踪框架中,将候选样本外观模型表示假设为由一组复合模板和最小重构误差组成的线性回归问题,首先利用经典的增量主成分分析法从在线高维数据中学习出一组低维子空间基向量(模板正样本),并根据前一时刻跟踪结果在线实时采样一些特殊的负样本加以扩充目标模板数据,再利用新组织的模板基向量和独立同分布的高斯—拉普拉斯混合噪声来线性拟合候选目标外观模型,最后估计出候选样本和真实目标之间的最大似然度,从而使跟踪器能够准确捕捉每一时刻的真实目标状态信息。结果 在一些公认测试视频序列上的实验结果表明,本文算法在目标模板学习和候选样本外观模型表示等方面比同类方法更能准确有效地反映出视频场景中目标状态的各种复杂变化,能够较好地解决各种不确定干扰因素下的模型退化和跟踪漂移问题,和一些优秀的同类算法相比,可以达到相同甚至更高的跟踪精度。结论 本文算法能够在线学习较为精准的目标模板并定期更新,使得跟踪器良好地适应内在或外在因素(姿态、光照、遮挡、尺度、背景扰乱及运动模糊等)所引起的视觉信息变化,始终保持其最佳的状态,使得候选样本外观模型的表示更加可靠准确,从而展现出更为鲁棒的性能。     

EXEM: Efficient XML data exchange management for mobile applications

In the past decade, the number of mobile devices has increased significantly. These devices are in turn showing more computational capabilities. It is therefore possible to envision a near future where client applications may be deployed on these devices. There are, however, constraints that hinder this deployment, especially the limited communication bandwidth and storage space available. This paper describes the Efficient XML Data Exchange Manager (EXEM) that combines context-dependent lossy and lossless compression mechanisms used to support lightweight exchange of objects in XML format between server and client applications. The lossy compression mechanism reduces the size of XML messages by using known information about the application. The lossless compression mechanism decouples data and metadata (compression dictionary) content. We illustrate the use of EXEM with a prototype implementation of the lossless compression mechanism that shows the optimization of the available resources on the server and the mobile client. These experimental results demonstrate the efficiency of the EXEM approach for XML data exchange in the context of mobile application development.

基于粒子滤波的全方位视觉传感器实现移动机器人导航

研究了一种引导机器人沿着固定轨迹运动的实时视觉伺服系统,并提出了一种实现移动机器人导航的创新的系统架构.系统由基于鱼眼镜头的全方位视觉传感器和嵌入式图像处理单元构成,可以实时校正鱼眼镜头畸变,并利用复合的粒子滤波算法识别和跟踪自定义的航标,最终实现移动机器人的导航.实验表明,该系统能够校正鱼眼镜头畸变,实时跟踪航标并有效实现机器人的定位和导航,且结构紧凑、功耗低,容易集成到各种移动设备中实现自主导航、安防监控等功能.     

A Reference Architecture to support the development of mobile applications based on self-adaptive services

Nowadays, most human daily tasks can be performed by means of Mobile Applications (MobApps). Devices running such applications have some limitations (e.g., processing and storage) compared to personal computers. Therefore, integration of MobApps into service-based systems has been a feasible alternative to overcome these limitations. Moreover, these applications must be prepared to deal with the changes at runtime (e.g., user’s new needs or modifications in their execution environment). In parallel, Reference Architectures (RA) have been used as an important way to support the development, standardization, and evolution of software systems. Although relevant, RA for the domain of MobApps based on services that require adaptation at runtime is still an issue to be explored in depth. This paper presents a RA for Self-MobApps (named RA4Self-MobApps), which aims to support the development of such applications. To show the applicability of our RA, a case study was conducted. As result, we observe our RA has good perspective to efficiently contribute to the Self-MobApps domain.     

Schema design and mapping strategies for persistent object models

A formal model is presented for a conceptual schema of persistent object models that support a strong notion of object identity. The object constructors in the model are sets, tuples, and disjunct. The databases that correspond to such schemata are graph-structured object spaces. These conceptual object spaces are mapped onto physical object spaces, which are typically forests of trees. The characteristics of the physical schemata are discussed and an algorithm to transform a conceptual schema into a physical schema is given.     

Alignment of a flexible sheet object with position-based and image-based visual servoing

This paper describes visual servoing methods to align an end edge of a flexible sheet object such as paper to a specified line segment in 3D space. In order to manipulate the end edge pose which may be distant from a grasping point by a robot hand on the flexible sheet, we incorporate online estimation of the relative pose between the end edge and the robot hand into visual servoing control laws. Two types of feature values to be regulated, position-based and image-based ones, are defined. The position-based one consists of 3D pose parameters of the end edge, which are estimated by fitting a polynomial surface model to stereo-measured edge points around the sheet. The image-based one consists of image pixel values within narrow regions around the end edge. Through numerical simulations, we confirm that the position-based features are effective in achieving quick response while the image-based features are robust against measurement noise. In order to combine these contrasting behaviors, we introduce a weighted combination of the position-based and image-based features. Experimental results show both of the position-based method and the weighted combination method work well and suggest the possibility that the weighted combination method can reduce final alignment errors.     

视觉注意机制在大视场目标快速定位中的应用

视觉心理学研究表明人类在看一个场景时,往往会在很短时间内找到几个显著区,然后再细看显著区域的内容,这样可以使得人类可以快速分析复杂图像。算法首先模拟人类视觉系统特点,根据图像的底层信息如对比度、方向、亮度等提取图像中几个最需要关注的显著区域,然后按照显著性由强到弱的顺序分别在每个显著区域利用具有尺度旋转不变性的对数极坐标变换方法进行目标的匹配定位。该方法在没有牺牲定位准确度的前提下,大幅减小了运算复杂度。实验表明该算法定位速度快而且准确。     

A communication infrastructure to ease the development of mobile collaborative applications

Mobile workers doing loosely coupled activities typically perform on demand collaboration in the physical workplace. Communication services available in such work scenarios are uncertain, therefore mobile collaborative applications supporting those activities must provide ad hoc communication mechanisms in order to use each cooperation opportunity. Typically, the complexity of implementing such mobile ad hoc communication mechanisms becomes a challenge that jeopardizes the development of mobile collaborative solutions. This article presents a communication infrastructure named HLMP API dealing with that challenge. HLMP API intends to ease the development of such applications through the reuse of communication services. The infrastructure is an application programming interface that implements the HLMP routing protocol and also some awareness mechanisms that are required for mobile loosely coupled work. Developers using this infrastructure do not have to perform low-level programming.     

结合双模板融合与孪生网络的鲁棒视觉目标跟踪

目的 视觉目标跟踪算法主要包括基于相关滤波和基于孪生网络两大类。前者虽然精度较高但运行速度较慢,无法满足实时要求。后者在速度和精度方面取得了出色的跟踪性能,然而,绝大多数基于孪生网络的目标跟踪算法仍然使用单一固定的模板,导致算法难以有效处理目标遮挡、外观变化和相似干扰物等情形。针对当前孪生网络跟踪算法的不足,提出了一种高效、鲁棒的双模板融合目标跟踪方法(siamese tracker with double template fusion,Siam-DTF)。方法 使用第1帧的标注框作为初始模板,然后通过外观模板分支借助外观模板搜索模块在跟踪过程中为目标获取合适、高质量的外观模板,最后通过双模板融合模块,进行响应图融合和特征融合。融合模块结合了初始模板和外观模板各自的优点,提升了算法的鲁棒性。结果 实验在3个主流的目标跟踪公开数据集上与最新的9种方法进行比较,在OTB2015(object tracking benchmark 2015)数据集中,本文方法的AUC(area under curve)得分和精准度分别为0.701和0.918,相比于性能第2的SiamRPN++(siamese region proposal network++)算法分别提高了0.6%和1.3%;在VOT2016(visual object tracking 2016)数据集中,本文方法取得了最高的期望平均重叠(expected average overlap,EAO)和最少的失败次数,分别为0.477和0.172,而且EAO得分比基准算法SiamRPN++提高了1.6%,比性能第2的SiamMask_E算法提高了1.1%;在VOT2018数据集中,本文方法的期望平均重叠和精确度分别为0.403和0.608,在所有算法中分别排在第2位和第1位。本文方法的平均运行速度达到47帧/s,显著超出跟踪问题实时性标准要求。结论 本文提出的双模板融合目标跟踪方法有效克服了当前基于孪生网络的目标跟踪算法的不足,在保证算法速度的同时有效提高了跟踪的精确度和鲁棒性,适用于工程部署与应用。     

显著性物体检测研究综述：方法、应用和趋势

显著性物体检测旨在快速定位图像中的显著性目标,可用于目标检测和识别、关键点定位、视觉跟踪、语义分割等计算机视觉任务中。为梳理显著性检测研究的发展脉络,从方法、应用领域和研究方向等方面分析显著性检测的研究现状和发展趋势。首先,阐述了显著性检测与相关研究的区别和联系;然后,分析了目前主流的显著性物体检测算法的流程、创新点、性能和适用性;接下来,介绍了显著性检测领域数据集的发展和演化;最后,展望了显著性检测研究的发展趋势并总结了显著性检测的主要应用领域。     

基于概率图与视觉显著性的海面目标检测方法

针对基于视觉的传统海面目标检测算法在水面无人艇的自动避碰应用中存在检测精确率、召回率低以及对复杂场景的适应性不足的问题,提出一种基于概率图与视觉显著性的海面目标检测算法。首先利用概率图模型分割出原始图像中的海界限区域与海面孤立目标;然后针对海界限区域子图像特点,设计了一种基于方向抑制的梯度特征,并结合背景先验改进频率调谐显著图,利用特征融合的方法提取海界限区域的潜在目标。实验结果表明,该算法能够有效抑制云、飞鸟、海天线和海杂波的背景干扰。与传统方法相比,提出的方法具有更高的精确率与召回率,且满足无人艇自动避碰实时性的要求。     

Offline time is quality time. Comparing within-group self-disclosure in mobile messaging applications and face-to-face interactions

In contrast to the prominent individualistic view on self-disclosure, this study focuses on self-disclosure in groups of prior acquaintances that both meet offline and communicate online. It compares within-group self-disclosure between offline face-to-face (FtF) interactions and online communication via mobile messaging applications (MMAs). An online-survey (N = 357) was conducted to test for differences between within-group self-disclosure online and offline across four dimensions (amount, depth, breadth, valence). The results show that there is more amount, more breadth and more depth for offline within-group self-disclosure, but it is less positively valenced than online within-group self-disclosure. Interestingly, the mere frequency of communication is higher in an MMA environment. In spite of the permanent availability of the online communication sphere, group members do not permanently disclose personal information to each other online. Thus, for within-group self-disclosure, offline time seems quality time.     

Perses: A framework for the continuous evaluation of the QoS of distributed mobile applications

The increasing capabilities of mobile devices have led to the emergence of new paradigms exploiting them. These paradigms foster the onload and distribution of functionalities on mobile devices, allowing the development of distributed mobile applications. This distribution reduces the latency and the data traffic overhead and improves privacy. As in any other mobile application, their success largely depends on the quality of service (QoS) they offer. Nevertheless, the evaluation of distributed mobile applications is particularly complex due to the number, heterogeneity, and interactions between the devices involved. Current techniques allow developers to assess the quality of a single device, but they are not designed for highly heterogeneous, distributed, and collaborative environments. This paper presents a framework called Perses, which allows the creation of virtual scenarios with multiple heterogeneous mobile devices to launch end-to-end tests to evaluate not only each device but also the interactions among them. The framework was evaluated against a real deployment, showing that the behavior and the quality attributes measured are similar to those of the real deployment, allowing developers to evaluate these applications before launching them. Finally, Perses was integrated into a DevOps methodology to automate its execution and further facilitate its adoption by software companies.     

视觉优化的移动三维图形自适应重构技术研究

为保证移动终端上生成满意的可视化结果,适应不同软硬件环境的要求,提出了一种基于视觉重要性的模型分层选择自适应绘制方法.该方法根据场景中对象的视觉重要性,自动调节不同级别细节层次模型的分布比例,满足限时计算机制的要求,使场景的生成时间保持较好的稳定性.在动态场景中对该方法进行的实验结果表明,该方法能在保证场景可视化真实感的基础上,有效提升场景的绘制速度,为移动终端图形绘制成本和视觉效果提供了一种折中解决方案.     

Status and trends of mobile-health applications for iOS devices: A developer's perspective

Modern smart mobile devices offer media-rich and context-aware features that are highly useful for electronic-health (e-health) applications. It is therefore not surprising that these devices have gained acceptance as target devices for e-health applications, turning them into m-health (mobile-health) apps. In particular, many e-health application developers have chosen Apple's iOS mobile devices such as iPad, iPhone, or iPod Touch as the target device to provide more convenient and richer user experience, as evidenced by the rapidly increasing number of m-health apps in Apple's App Store. In this paper, the top two hundred of such apps from the App Store were examined from a developer's perspective to provide a focused overview of the status and trends of iOS m-health apps and an analysis of related technology, architecture, and user interface design issues. The top 200 apps were classified into different groups according to their purposes, functions, and user satisfaction. It was shown that although the biggest group of apps was medical information reference apps that were delivered from or related to medical articles, websites, or journals, mobile users disproportionally favored tracking tools. It was clear that m-health apps still had plenty of room to grow to take full advantage of unique mobile platform features and truly fulfill their potential. In particular, introduction of two- or three-dimensional visualization and context-awareness could further enhance m-health app's usability and utility. This paper aims to serve as a reference point and guide for developers and practitioners interested in using iOS as a platform for m-health applications, particular from the technical point of view.     

Discrete-event simulation for efficient and stable resource allocation in collaborative mobile cloudlets

The deployment of highly interactive, media-rich applications on mobile devices is hindered by the inherent limitations on compute power, memory and battery capacity of these hand-held platforms. The cloudlet concept, opportunistically offloading computation to nearby devices, has proven to be a viable solution in offering resource-intensive applications on mobile devices. In this paper, we propose to extend the cloudlet concept with collaborative scenarios, in which not only hardware resources for processing are shared between all cloudlet users, but also the data computed.In a cloudlet, the resource demand should be spread over all available cloudlet nodes. User mobility and fluctuations in wireless bandwidth will cause the optimal resource allocation to vary over time. The cloudlet middleware must continuously balance the performance gain of reallocating components with the operational costs in terms of user experience and management complexity. In this paper, we formulate this optimization problem based on a theoretical cloudlet model capturing the infrastructure, application structure and user behavior.In order to solve this problem, two heuristic allocation algorithms based on Steepest Descent (SD) and Simulated Annealing (SA) are described. Besides optimality of the found solution, it is also important to limit the number of reallocations at runtime. To evaluate the performance and stability of the algorithms, we propose a discrete-event model for cloudlet simulation. For multiple application scenarios, we observe that SD performs 4 times less reallocations than SA. By introducing hysteresis, the number of reallocations by SA can be nearly halved without any significant degradation of application performance.