面向智能驾驶的平行视觉感知：基本概念、框架与应用

目的 视觉感知技术是智能车系统中的一项关键技术,但是在复杂挑战下如何有效提高视觉性能已经成为智能驾驶领域的重要研究内容。本文将人工社会（artificial societies）、计算实验（computational experiments）和平行执行（parallel execution）构成的ACP方法引入智能驾驶的视觉感知领域,提出了面向智能驾驶的平行视觉感知,解决了视觉模型合理训练和评估问题,有助于智能驾驶进一步走向实际应用。方法 平行视觉感知通过人工子系统组合来模拟实际驾驶场景,构建人工驾驶场景使之成为智能车视觉感知的“计算实验室”;借助计算实验两种操作模式完成视觉模型训练与评估;最后采用平行执行动态优化视觉模型,保障智能驾驶对复杂挑战的感知与理解长期有效。结果 实验表明,目标检测的训练阶段虚实混合数据最高精度可达60.9%,比单纯用KPC（包括：KITTI（Karlsruhe Institute of Technology and Toyota Technological Institute）,PASCAL VOC（pattern analysis,statistical modelling and computational learning visual object classes）和MS COCO（Microsoft common objects in context））数据和虚拟数据分别高出17.9%和5.3%;在评估阶段相较于基准数据,常规任务（-30°且垂直移动）平均精度下降11.3%,环境任务（雾天）平均精度下降21.0%,困难任务（所有挑战）平均精度下降33.7%。结论 本文为智能驾驶设计和实施了在实际驾驶场景难以甚至无法进行的视觉计算实验,对复杂视觉挑战进行分析和评估,具备加强智能车在行驶过程中感知和理解周围场景的意义。     

A framework for variation visualization and understanding in complex manufacturing systems

This paper provides a framework that allows industrial practitioners to visualize the most significant variation patterns within their process using three-dimensional animation software. In essence, this framework complements Phase I statistical monitoring methods by enabling users to: (1) acquire detailed understanding of common-cause variability (especially in complex manufacturing systems); (2) quickly and easily visualize the effects of common-cause variability in a process with respect to the final product; and (3) utilize the new insights regarding the process variability to identify opportunities for process improvement. The framework is illustrated through a case study using actual dimensional data from a US automotive assembly plant.     

Historical perception as a complementary framework for understanding the usability of mobile computers

This paper suggests a social-psychological framework for understanding the usability of mobile computers. This framework complements and extends extant sociological explanations of mobile computing. Sociological explanations satisfy principles of pragmatism and ubiquity in judging the usability of mobile computers. The paper argues that sociological explanations are inadequate, and draws upon the historical epistemology of perception to propose social-psychological explanations to complement them. By this epistemology, a user’s perception is deemed as a mode of action that is mediated by historical or functional representations. These issues are illustrated in an empirical case of the use of personal digital assistants (PDAs) in hospitals of the British National Health Service. The historical epistemology of perception suggests the principle of representation to complement the existing principles of ubiquity and pragmatism. This suggestion is derived from an analysis of the complementation between the user’s perception, work and movement which are conscious actions enacted concurrently during the use of mobile computers. Implications for the implementation and evaluation of mobile computing projects are provided.     

平行系统方法与复杂系统的管理和控制

提出平行系统方法的基本思想、概念和运行的基本框架，并讨论了控制系统与平行系统的关系和异同之处，平行系统是控制系统和计算机仿真随着系统复杂程度的增加以及计算技术和分析方法的进一步发展而必然迈上的一个更高的台阶，是弥补很难甚至无法对复杂系统进行精确建模和实验之不足的一种有效手段，也是对复杂系统进行管理和控制的一种可行方式。     

Modeling, animating, and rendering complex scenes using volumetrictextures

Complex repetitive scenes containing forests, foliage, grass, hair, or fur, are challenging for common modeling and rendering tools. The amount of data, the tediousness of modeling and animation tasks, and the cost of realistic rendering have caused such kind of scene to see only limited use even in high-end productions. The author describes how the use of volumetric textures is well suited to such scenes. These primitives can greatly simplify modeling and animation tasks. More importantly, they can be very efficiently rendered using ray tracing with few aliasing artifacts. The main idea, initially introduced by Kajiya and Kay (1989), is to represent a pattern of 3D geometry in a reference volume, that is tiled over an underlying surface much like a regular 2D texture. In our contribution, the mapping is independent of the mesh subdivision, the pattern can contain any kind of shape, and it is prefiltered at different scales as for MIP-mapping. Although the model encoding is volumetric, the rendering method differs greatly from traditional volume rendering. A volumetric texture only exists in the neighborhood of a surface, and the repeated instances (called texels) of the reference volume are spatially deformed. Furthermore, each voxel of the reference volume contains a key feature which controls the reflectance function that represents aggregate intravoxel geometry. This allows for ray tracing of highly complex scenes with very few aliasing artifacts, using a single ray per pixel (for the part of the scene using the volumetric texture representation). The major technical considerations of our method lie in the ray-path determination and in the specification of the reflectance function     

A robust framework for joint background/foreground segmentation of complex video scenes filmed with freely moving camera

This paper explores a robust region-based general framework for discriminating between background and foreground objects within a complex video sequence. The proposed framework works under difficult conditions such as dynamic background and nominally moving camera. The originality of this work lies essentially in our use of the semantic information provided by the regions while simultaneously identifying novel objects (foreground) and non-novel ones (background). The information of background regions is exploited to make moving objects detection more efficient, and vice-versa. In fact, an initial panoramic background is modeled using region-based mosaicing in order to be sufficiently robust to noise from lighting effects and shadowing by foreground objects. After the elimination of the camera movement using motion compensation, the resulting panoramic image should essentially contain the background and the ghost-like traces of the moving objects. Then, while comparing the panoramic image of the background with the individual frames, a simple median-based background subtraction permits a rough identification of foreground objects. Joint background-foreground validation, based on region segmentation, is then used for a further examination of individual foreground pixels intended to eliminate false positives and to localize shadow effects. Thus, we first obtain a foreground mask from a slow-adapting algorithm, and then validate foreground pixels (moving visual objects + shadows) by a simple moving object model built by using both background and foreground regions. The tests realized on various well-known challenging real videos (across a variety of domains) show clearly the robustness of the suggested solution. This solution, which is relatively computationally inexpensive, can be used under difficult conditions such as dynamic background, nominally moving camera and shadows. In addition to the visual evaluation, spatial-based evaluation statistics, given hand-labeled ground truth, has been used as a performance measure of moving visual objects detection.     

面向室内场景的主被动融合视觉定位系统

目的 视觉定位旨在利用易于获取的RGB图像对运动物体进行目标定位及姿态估计。室内场景中普遍存在的物体遮挡、弱纹理区域等干扰极易造成目标关键点的错误估计,严重影响了视觉定位的精度。针对这一问题,本文提出一种主被动融合的室内定位系统,结合固定视角和移动视角的方案优势,实现室内场景中运动目标的精准定位。方法 提出一种基于平面先验的物体位姿估计方法,在关键点检测的单目定位框架基础上,使用平面约束进行3自由度姿态优化,提升固定视角下室内平面中运动目标的定位稳定性。基于无损卡尔曼滤波算法设计了一套数据融合定位系统,将从固定视角得到的被动式定位结果与从移动视角得到的主动式定位结果进行融合,提升了运动目标的位姿估计结果的可靠性。结果 本文提出的主被动融合室内视觉定位系统在iGibson仿真数据集上的平均定位精度为2～3 cm,定位误差在10 cm内的准确率为99%;在真实场景中平均定位精度为3～4 cm,定位误差在10 cm内的准确率在90%以上,实现了cm级的定位精度。结论 提出的室内视觉定位系统融合了被动式和主动式定位方法的优势,能够以较低设备成本实现室内场景中高精度的目标定位结果,并在遮挡、目标...     

A vision system for symbolic interpretation of dynamic scenes using arsom

We describe an artificial high-level vision system for the symbolic interpretation of data coming from a video camera that acquires the image sequences of moving scenes. The system is based on ARSOM neural networks that learn to generate the perception-grounded predicates obtained by image sequences. The ARSOM neural networks also provide a three-dimensional estimation of the movements of the relevant objects in the scene. The vision system has been employed in two scenarios: the monitoring of a robotic arm suitable for space operations, and the surveillance of an electronic data processing (EDP) center.     

RFID,privacy and the perception of risk: A strategic framework

Against the background of the first RFID-Rollouts by large retailers in North America and Europe, this paper concerns itself with the perception of RFID technology as a risk to privacy. The objective of our contribution is to identify, at a relatively early phase of the risk development, strategic options with which RFID suppliers and users can positively influence the public acceptance of the technology. We propose a strategic framework based on research findings on risk perception and technology acceptance as well as a set of options for coping with the public perception of RFID-related privacy risks.     

Toward local and global perception modules for vision substitution

Although retinal neural implants have considerably progressed they raise a number of questions concerning user acceptance, risk rejection, and cost. For the time being we support a low cost approach based on the transmission of limited vision information by means of the auditory channel. The See ColOr mobility aid for visually impaired individuals transforms a small portion of a coloured video image into sound sources represented by spatialised musical instruments. Basically, the conversion of colours into sounds is achieved by quantisation of the HSL colour system. Our purpose is to provide blind people with a capability of perception of the environment in real time. In this work the novelty is the simultaneous sonification of colour and depth, the last parameter being coded by sound rhythm. The main drawback of our approach is that the sonification of a limited portion of a captured image involves limited perception. As a consequence, we propose to extend the local perception module by introducing a new global perception module aiming at providing the user with a clear picture of the entire scene characteristics. Finally, we present several experiments to illustrate the limited perception module, such as: (1) detecting an open door in order to go out from the office; (2) walking in a hallway and looking for a blue cabinet; (3) walking in a hallway and looking for a red tee shirt; (4) avoiding two red obstacles; (5) moving outside and avoiding a parked car. Videos of experiments are available on http://www.youtube.com/guidobologna.     

图像理解原理的数学评价

图像是一种客观存在的事物,它以不同的模式向人们传递信息.图像理解就是模式分析和理解,是一门研究用计算机系统分析和理解图像,实现类似人类视觉系统理解外部世界的学科.介绍了图像理解的基本概念、原理以及与相关学科的联系和区别,综合分析总结了目前在图像恢复、图像分割及特征提取中常见的多种算法的特点,并且对图像理解的应用发展进行了一定的展望.     

Parallel manipulators: state of the art and perspectives

Parallel manipulators have been increasingly developed over the last few years from a theoretical view point as well as for practical applications. In this paper, recent advances are summarized and various applications for this kind of manipulator are illustrated.     

Human performance in industrial scheduling: A framework for understanding

Planning and scheduling activities have a significant impact on the performance of manufacturing enterprises. Throughout the 1980s there was a belief that computer‐led solutions would “solve” complex industrial planning and scheduling problems. However, in most manufacturing organizations, planning and scheduling still require significant human support to ensure effective performance. Although the contribution of these human resources is often highly valued, we are only beginning to develop a coherent body of knowledge that can contribute toward the successful integration of human and computer‐based planning and scheduling systems. Here we examine the state of knowledge in this domain and identify the need for field investigations. We present a framework to facilitate research in human and organizational issues in planning and scheduling in manufacturing. A structured and detailed set of research questions is developed to underpin field studies. The framework focuses on understanding the scheduling environment, the process of scheduling, and related performance issues. The application of the framework is illustrated using our own field studies, where a number of specific research questions of practical importance have been identified: what scheduling is, who carries it out, what influences scheduling practice and performance, how schedulers actually schedule, what makes a good scheduler and schedule, and what support is needed. The framework makes a valuable contribution to advancing knowledge in an area of real practical benefit to contemporary manufacturing industry. © 2001 John Wiley & Sons, Inc.     

海量视频人脸提取与识别并行框架设计及优化

近年来,监控设备大量应用于城市智能化建设中,而其产生的海量视频数据,亟待一种快速高效的解决方案。随着大数据处理技术的发展,使得处理海量视频数据成为可能。本文将视频数据集解耦合实现任务的并行处理,通过Spark读取数据流的同时获取关键帧的方式解决了解耦视频数据引起数据倍增问题,并对图片特征数据进行优化,进而在Spark上实现了具有高可扩展性并行处理海量视频数据的框架。本文在天河二号云平台上进行部署实验,分析实验结果表明随着处理节点个数增加本框架可以获得近线性的加速比。     

Seeing data: new methods for understanding information

Cutting-edge information strategies demonstrate that visualization can help make abstract data more accessible by geographically representing relationships between data pieces and visually bringing out hidden features and relationships. Demonstrating the potential of information visualization to make the lives of general users easier a wide variety of development projects - many of which use different presentation strategies for representing data - continue to explore new techniques to help users map data variable onto multiple axes.     

The recovery and understanding of a line drawing from indoor scenes

A general procedure for the understanding of a class of indoor scenes is proposed. The suggested algorithm makes use of an extensive 2-D processing of the image that provides a faithful line drawing of the viewed scene. It also uses procedures adequate for the understanding of the 3-D structure and for the recognition of several items in the scene. The approach is specific for indoor scenes, such as corridors, offices, and laboratory rooms, where long straight edges are predominant and vanishing points can be detected     

Interaction framework for home environment using speech and vision

In this article we describe an interaction framework that uses speech recognition and computer-vision to model new generation of interfaces in the residential environment. We outline the blueprints of the architecture and describe the main building blocks. We show a concrete prototype platform where this novel architecture has been deployed and tested at the user field trials. The work is co-funded by EC as part of “HomeTalk” IST-2001-33507 project.     

Theory of edge perception for computer vision feedback control

In this paper, the authors address the problem of edge-perception for its applications to vision-feedback control in robotic systems.In natural vision, the recognition of objects takes place through the process consisting of eye system, neural networks and cognition. The cognitive process, in turn yields a phenomenon known as perception. This is the phenomenon of perception of physical attributes, such as edges, color and texture, etc., which is responsible for the recognition of objects through the natural vision processes.In this paper, we make an attempt to postulate the theory of perception for gray-level images. The gray-level images, when going through the cognitive and perception processes, are contaminated by the uncertainty; here we call it cognitive uncertainty.The studies in this paper are confined to the phenomenon of edge-perception for two-dimensional gray-level images, however, these studies can be extended to other types of visual attributes both in two-dimensional and three-dimensional spaces. Indeed, the perception of these attributes, which attempts to emulate the human vision system, may help in the design of a truly robust computer vision-feedback control system for robotic applications.