959 resultados para space variant active vision


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Educating responsive graduates. Graduate competencies include reliability, communication skills and ability to work in teams. Students using Collaborative technologies adapt to a new working environment, working in teams and using collaborative technologies for learning. Collaborative Technologies were used not simply for delivery of learning but innovatively to supplement and enrich research-based learning, providing a space for active engagement and interaction with resources and team. This promotes the development of responsive ‘intellectual producers’, able to effectively communicate, collaborate and negotiate in complex work environments. Exploiting technologies. Students use ‘new’ technologies to work collaboratively, allowing them to experience the reality of distributed workplaces incorporating both flexibility and ‘real’ time responsiveness. Students are responsible and accountable for individual and group work contributions in a highly transparent and readily accessible workspace. This experience provides a model of an effective learning tool. Navigating uncertainty and complexity. Collaborative technologies allows students to develop critical thinking and reflective skills as they develop a group product. In this forum students build resilience by taking ownership and managing group work, and navigating the uncertainties and complexities of group dynamics as they constructively and professionally engage in team dialogue and learn to focus on the goal of the team task.

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Negabinary is a component of the positional number system. A complete set of negabinary arithmetic operations are presented, including the basic addition/subtraction logic, the two-step carry-free addition/subtraction algorithm based on negabinary signed-digit (NSD) representation, parallel multiplication, and the fast conversion from NSD to the normal negabinary in the carry-look-ahead mode. All the arithmetic operations can be performed with binary logic. By programming the binary reference bits, addition and subtraction can be realized in parallel with the same binary logic functions. This offers a technique to perform space-variant arithmetic-logic functions with space-invariant instructions. Multiplication can be performed in the tree structure and it is simpler than the modified signed-digit (MSD) counterpart. The parallelism of the algorithms is very suitable for optical implementation. Correspondingly, a general-purpose optical logic system using an electron trapping device is suggested. Various complex logic functions can be performed by programming the illumination of the data arrays without additional temporal latency of the intermediate results. The system can be compact. These properties make the proposed negabinary arithmetic-logic system a strong candidate for future applications in digital optical computing with the development of smart pixel arrays. (C) 1999 Society of Photo-Optical Instrumentation Engineers. [S0091-3286(99)00803-X].

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提出了菲涅耳联合变换相关器(Fresnel Joint Trans form Correlator,FnJTC)结构,给出了数学推导过程,并通过计算机模拟验证了可行性及其与传统相关器所不同的相关特性。在相关过程第一阶段中,菲涅耳联合变换相关器对输入的联合图像作菲涅耳变换,代替了传统联合变换相关器(JTC)的傅里叶变换。与传统相关器相比,菲涅耳联合变换相关器是空变系统,相关峰值依赖于输入参考图像与目标图像的相似性、两图像之间的相对位置及参考图像(或目标图像)的线性相位调制。

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We experimentally demonstrate the planar focusing of Surface Plasmon Polaritons using space variant PMMA subwavelength features on top of a metallic film. Focusing is obtained by creating an effective graded refractive index profile. © 2012 OSA.

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We experimentally demonstrate the planar focusing of Surface Plasmon Polaritons using space variant PMMA subwavelength features on top of a metallic film. Focusing is obtained by creating an effective graded refractive index profile. © OSA 2012.

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运动目标跟踪技术是未知环境下移动机器人研究领域的一个重要研究方向。该文提出了一种基于主动视觉和超声信息的移动机器人运动目标跟踪设计方法,利用一台SONY EV-D31彩色摄像机、自主研制的摄像机控制模块、图像采集与处理单元等构建了主动视觉系统。移动机器人采用了基于行为的分布式控制体系结构,利用主动视觉锁定运动目标,通过超声系统感知外部环境信息,能在未知的、动态的、非结构化复杂环境中可靠地跟踪运动目标。实验表明机器人具有较高的鲁棒性,运动目标跟踪系统运行可靠。

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利用SONYEV-D31摄像机和自主研发的摄像机控制模块,构建了一套主动视觉子系统,并将该子系统应用于RIRA-II型移动机器人上,实现了移动机器人运动目标自动跟踪功能。RIRA-II移动机器人采用了由一组分布式行为模块和集中命令仲裁器组成的基于行为的分布式控制体系结构。各行为模块基于领域知识通过反应方式产生投票,由仲裁器产生动作指令,机器人完成相应的动作。在设置了障碍、窄通道以及模拟墙体的复杂环境下进行运动目标跟踪实验,实验表明运动目标跟踪系统运行可靠,具有较高的鲁棒性。

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设计了一种基于多微处理器的智能超声探测系统。该系统采用由上位工作模式控制单元和下位智能超声传感器阵列组成的分布式结构。每个超声传感器均由独立的微处理器控制,并完成实时数据处理、抗干扰处理、故障报警以及数据通信等功能。上位控制单元根据移动机器人的运动状态采用不同的控制策略,使下位传感器阵列分组并行工作,提高了探测系统的实时性;下位传感器采用"阈值比较法"、"改进型递推均值滤波"算法和模糊信息处理技术,提高了探测系统的准确性、可靠性。将该探测系统安装于RIRA-II移动机器人上,进行了基于主动视觉和超声信息的运动目标跟踪实验,实验表明超声探测系统运行可靠、稳定。

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本文提出了一种基于人工神经网络的多线阵相机系统标定与 3D定位方法 ,并应用于基于多线阵相机构成的视觉空间定位系统 .该视觉定位系统利用了线阵相机的快速性与高分辨率的特点 ,非平行空间投影面相交定位的基本原理 ,实现了这种结构下快速、高精度空间定位 .实验表明 ,人工神经网络的定位方法简化了多线阵视觉定位系统标定与定位计算的复杂性 ,在定位精度上达到了良好效果 .为机器人位置反馈控制提供了有效的技术途径

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This research project is a study of the role of fixation and visual attention in object recognition. In this project, we build an active vision system which can recognize a target object in a cluttered scene efficiently and reliably. Our system integrates visual cues like color and stereo to perform figure/ground separation, yielding candidate regions on which to focus attention. Within each image region, we use stereo to extract features that lie within a narrow disparity range about the fixation position. These selected features are then used as input to an alignment-style recognition system. We show that visual attention and fixation significantly reduce the complexity and the false identifications in model-based recognition using Alignment methods. We also demonstrate that stereo can be used effectively as a figure/ground separator without the need for accurate camera calibration.

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Computer vision for realtime applications requires tremendous computational power because all images must be processed from the first to the last pixel. Ac tive vision by probing specific objects on the basis of already acquired context may lead to a significant reduction of processing. This idea is based on a few concepts from our visual cortex (Rensink, Visual Cogn. 7, 17-42, 2000): (1) our physical surround can be seen as memory, i.e. there is no need to construct detailed and complete maps, (2) the bandwidth of the what and where systems is limited, i.e. only one object can be probed at any time, and (3) bottom-up, low-level feature extraction is complemented by top-down hypothesis testing, i.e. there is a rapid convergence of activities in dendritic/axonal connections.

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The goal of the project "SmartVision: active vision for the blind" is to develop a small and portable but intelligent and reliable system for assisting the blind and visually impaired while navigating autonomously, both outdoor and indoor. In this paper we present an overview of the prototype, design issues, and its different modules which integrate a GIS with GPS, Wi-Fi, RFID tags and computer vision. The prototype addresses global navigation by following known landmarks, local navigation with path tracking and obstacle avoidance, and object recognition. The system does not replace the white cane, but extends it beyond its reach. The user-friendly interface consists of a 4-button hand-held box, a vibration actuator in the handle of the cane, and speech synthesis. A future version may also employ active RFID tags for marking navigation landmarks, and speech recognition may complement speech synthesis.