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首页> 外文会议>2014 International Symposium on Optomechatronic Technologies >Advanced Methods for High-Speed Template Matching Targeting FPGAs
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Advanced Methods for High-Speed Template Matching Targeting FPGAs

机译：高速模板匹配目标FPGA的高级方法

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摘要

Template matching is an important image processing algorithm for object detection and tracking tasks especially because of its very high accuracy. Yet, one major disadvantage of this algorithm is its very high computational effort due to its high complexity which results in low update rates using conventional software-based systems. Additionally, these systems are often afflicted by latency and jitter. Pre-calculating small and robust templates allows for using FPGA-based template matching as an approach to solve these problems. Therefore, the paper outlines three successive software-based approaches to find these small and robust templates. The first approach contains the basic algorithm and is refined by the following two approaches using pre-processing. The resulting templates allow for using the programmable hardware of an FPGA to cache necessary image information and, more importantly, to derive the best matching of template and source image, which results in high update rates. This paper shows novel approaches to high-speed template matching on FPGAs. The validation of these approaches has shown that the resulting tracking quality and feasibility is highly dependent on the relative size of the template in regard to the object to track. The results show tracking uncertainties between one single pixel for low and hundreds of pixels for high resolution videos.
机译：模板匹配是用于对象检测和跟踪任务的重要图像处理算法，尤其是由于其非常高的准确性。然而，该算法的一个主要缺点是由于其高复杂度而导致其非常高的计算工作量，这导致使用传统的基于软件的系统导致较低的更新率。此外，这些系统通常受延迟和抖动的困扰。预先计算小型且健壮的模板，可以使用基于FPGA的模板匹配作为解决这些问题的方法。因此，本文概述了三种连续的基于软件的方法来查找这些小型且健壮的模板。第一种方法包含基本算法，并通过使用预处理的以下两种方法进行完善。生成的模板允许使用FPGA的可编程硬件来缓存必要的图像信息，更重要的是，可以导出模板和源图像的最佳匹配，从而提高了更新速度。本文展示了在FPGA上进行高速模板匹配的新颖方法。这些方法的验证表明，所产生的跟踪质量和可行性在很大程度上取决于模板相对于跟踪对象的相对大小。结果显示低分辨率的单个像素与高分辨率视频的数百个像素之间的跟踪不确定性。

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