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Adaptable Model-Based Tracking Using Analysis-by-Synthesis Techniques

机译:使用综合分析技术的基于模型的自适应跟踪

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摘要

In this paper we present a novel analysis-by-synthesis approach for real-time camera tracking in industrial scenarios. The camera pose estimation is based on the tracking of line features which are generated dynamically in every frame by rendering a polygonal model and extracting contours out of the rendered scene. Different methods of the line model generation are investigated. Depending on the scenario and the given 3D model either the image gradient of the frame buffer or discontinuities of the z-buffer and the normal map are used for the generation of a 2D edge map. The 3D control points on a contour are calculated by using the depth value stored in the z-buffer. By aligning the generated features with edges in the current image, the extrinsic parameters of the camera are estimated. The camera pose used for rendering is predicted by a line-based frame-to-frame tracking which takes advantage of the generated edge features. The method is validated and evaluated with the help of ground-truth data as well as real image sequences.
机译:在本文中,我们提出了一种新颖的综合分析方法,用于工业场景中的实时摄像机跟踪。相机姿态估计基于对线特征的跟踪,这些线特征是通过渲染多边形模型并从渲染的场景中提取轮廓而在每一帧中动态生成的。研究了线模型生成的不同方法。根据场景和给定的3D模型,帧缓冲区的图像梯度或z缓冲区和法线贴图的不连续性均用于生成2D边缘贴图。通过使用存储在z缓冲区中的深度值来计算轮廓上的3D控制点。通过将生成的特征与当前图像中的边缘对齐,可以估算相机的外部参数。用于渲染的相机姿态是通过基于行的逐帧跟踪来预测的,该跟踪利用了生成的边缘特征。该方法已通过地面数据和真实图像序列的验证和评估。

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