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An FPGA Processor for Real-Time, Fixed-Point Refinement of CDVS Keypoints

机译:用于实时的FPGA处理器,CDVs关键点的固定点细化

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Computer Vision is a more and more pervasive technology in nowadays image and video processing applications: examples include image driven search, stereoscopical matching, panorama stitching and industrial automation. Compact Descriptors for Visual Search (CDVS) is an algorithm for Computer Vision recently proposed as part of the MPEG-7 standard: it has the ability to select points of interest in the image (also referred to as keypoints) that exhibit robustness, in a certain degree, with respect to changes like homogeneous variations in luminance, changes in point of view, rotations, rescaling and geometrical distortion of the image. Keypoint Refinement is a phase of the CDVS algorithm which is aimed at discarding candidate keypoints that are likely to be unstable for their algebraic properties. This paper presents an FPGA circuit design that implements this phase on fixed point data with real time compatible throughput. Implementation results show a negligible impact on resources allocation even on mid-sized FPGAs.
机译:计算机Vision是一种越来越多的普遍技术,在如今的图像和视频处理应用中:示例包括图像驱动的搜索,立体匹配,全景拼接和工业自动化。用于视觉搜索(CDV)的紧凑描述符是最近提出的计算机视觉的算法,作为MPEG-7标准的一部分:它能够选择展示稳健性的图像中的兴趣点(也称为关键点)一定程度,关于亮度的均匀变化等变化,图像的视角变化,旋转,重构和图像的几何变形。关键点细化是CDVS算法的一个阶段,该算法旨在丢弃可能对其代数属性不稳定的候选键盘。本文介绍了一个FPGA电路设计,它在具有实时兼容吞吐量的固定点数据上实现此阶段。即使在中尺寸的FPGA上,实施结果表明对资源分配的影响忽略不计。

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