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Proceeding of the ... Conference on Computer and Robot Vision. Conference on Computer and Robot Vision最新文献

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Self-Localization at Street Intersections. 十字路口的自我定位。
Giovanni Fusco, Huiying Shen, James M Coughlan

There is growing interest among smartphone users in the ability to determine their precise location in their environment for a variety of applications related to wayfinding, travel and shopping. While GPS provides valuable self-localization estimates, its accuracy is limited to approximately 10 meters in most urban locations. This paper focuses on the self-localization needs of blind or visually impaired travelers, who are faced with the challenge of negotiating street intersections. These travelers need more precise self-localization to help them align themselves properly to crosswalks, signal lights and other features such as walk light pushbuttons. We demonstrate a novel computer vision-based localization approach that is tailored to the street intersection domain. Unlike most work on computer vision-based localization techniques, which typically assume the presence of detailed, high-quality 3D models of urban environments, our technique harnesses the availability of simple, ubiquitous satellite imagery (e.g., Google Maps) to create simple maps of each intersection. Not only does this technique scale naturally to the great majority of street intersections in urban areas, but it has the added advantage of incorporating the specific metric information that blind or visually impaired travelers need, namely, the locations of intersection features such as crosswalks. Key to our approach is the integration of IMU (inertial measurement unit) information with geometric information obtained from image panorama stitchings. Finally, we evaluate the localization performance of our algorithm on a dataset of intersection panoramas, demonstrating the feasibility of our approach.

智能手机用户越来越希望能够在各种与寻路、旅行和购物相关的应用程序中确定自己在环境中的精确位置。虽然GPS提供了有价值的自我定位估计,但在大多数城市位置,其精度仅限于大约10米。本文主要研究盲人或视障人士在过十字路口时的自我定位需求。这些旅行者需要更精确的自我定位,以帮助他们正确地调整自己与人行横道,信号灯和其他功能,如步行灯按钮。我们展示了一种新的基于计算机视觉的定位方法,该方法是为街道交叉口领域量身定制的。与大多数基于计算机视觉的定位技术不同,这些技术通常假设存在详细的、高质量的城市环境3D模型,我们的技术利用简单的、无处不在的卫星图像(例如,谷歌地图)来创建每个十字路口的简单地图。这种技术不仅可以自然地适用于城市地区的绝大多数街道十字路口,而且还具有附加的优势,即纳入盲人或视障旅行者所需的特定度量信息,即十字路口特征(如人行横道)的位置。该方法的关键是将IMU(惯性测量单元)信息与从图像全景拼接中获得的几何信息相结合。最后,我们在交叉全景数据集上评估了我们算法的定位性能,证明了我们方法的可行性。
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引用次数: 7
Stochastically Optimal Epipole Estimation in Omnidirectional Images with Geometric Algebra 基于几何代数的全向图像随机最优极点估计
Christian Gebken, G. Sommer
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引用次数: 2
Visual Navigation of Mobile Robot Using Optical Flow and Visual Potential Field 基于光流和视觉势场的移动机器人视觉导航
N. Ohnishi, A. Imiya
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引用次数: 10
Terrain-Based Sensor Selection for Autonomous Trail Following 基于地形的自主跟踪传感器选择
C. Rasmussen, Donald Scott
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引用次数: 6
Differential Geometry of Monogenic Signal Representations 单基因信号表示的微分几何
Lennart Wietzke, G. Sommer, Christian Schmaltz, J. Weickert
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引用次数: 16
Modeling and Tracking Line-Constrained Mechanical Systems 建模和跟踪线约束机械系统
B. Rosenhahn, T. Brox, D. Cremers, H. Seidel
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引用次数: 7
Fast Line-Segment Extraction for Semi-dense Stereo Matching 半密集立体匹配快速线段提取
Brian McKinnon, J. Baltes
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引用次数: 2
Generic Object Recognition Using Boosted Combined Features 使用增强组合特征的通用对象识别
D. Hegazy, Joachim Denzler
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引用次数: 7
An Approximate Algorithm for Solving the Watchman Route Problem 求解守望者路线问题的一种近似算法
Fajie Li, R. Klette
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引用次数: 16
Belief-Propagation on Edge Images for Stereo Analysis of Image Sequences 用于图像序列立体分析的边缘图像信念传播
Shushi Guan, R. Klette
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引用次数: 30
期刊
Proceeding of the ... Conference on Computer and Robot Vision. Conference on Computer and Robot Vision
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