VisiTrack -基于视频的实时增量跟踪

N. Esau, B. Kleinjohann, L. Kleinjohann, Dirk Stichling
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引用次数: 5

摘要

提出了一种基于视频的实时增量跟踪的新方法VisiTrack。VisiTrack开发的主要目标是设计或选择适合嵌入式实时计算的算法。我们特别关注延迟减少和存储最小化,因为算法应该在带有适当扩展的pda等移动设备上实时运行,即主要是相机。详细介绍了VisiTrack的图像分析、位置定位和误差最小化。对于VisiTrack的图像分析算法,定义并应用了线性处理和增量并发两大原则,以满足实时约束和降低系统延迟。为满足实时性要求,定位基于三维世界坐标与二维图像坐标的线性变换。然后成功地应用了基于卡尔曼滤波的实时误差最小化方法。VisiTrack应用于增强现实领域和机器人自我定位领域。
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VisiTrack - video based incremental tracking in real time
This paper presents VisiTrack, a novel approach for video based incremental tracking in real time. The major objectives in the development of VisiTrack was to design or select algorithms that are well suited for embedded real time computation. We had a special focus on latency reduction and storage minimization since the algorithms should run on mobile devices like PDAs with the appropriate extension, i.e. mainly a camera, in real time. The image analysis, position localization and error minimization of VisiTrack are explained in detail. For the image analysis algorithms of VisiTrack two major principles, linear processing and incremental concurrency, were defined and applied in order to fulfill real time constraints and reduce system latency. In order to meet real time requirements the position localization is based on a linear transformation between 3D world coordinates and 2D image coordinates. Afterwards a real time error minimization based on the Kalman filter is applied successfully. VisiTrack is applied in the Augmented Reality domain and in the field of robotic self localization.
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