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摘要翻译：
视觉目标跟踪是计算机视觉领域的一个活跃课题，其应用范围广泛。构建目标跟踪器所需的主要子任务（如目标检测、特征提取和目标跟踪）都是计算密集型的。此外，跟踪器的实时操作对其几乎所有的应用都是不可或缺的。因此，为了更好地实现跟踪器，需要采用完整的硬件或硬件/软件协同设计方法。本文介绍了近二十年来目标跟踪器硬件实现的文献综述。虽然文献中有几个跟踪调查，但缺少针对不同跟踪器的硬件实现的调查。我们相信，本研究将填补现有研究的空白，并对如何设计高效的跟踪器进行完善，同时指出研究人员在这一领域的未来发展方向。我们强调缺乏硬件实现的最先进的跟踪算法以及增强的经典算法。我们还强调了测量基于硬件的跟踪器的跟踪性能的必要性。此外，需要提供足够的基于硬件的跟踪器的细节，以便在不同的实现之间进行合理的比较。
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英文标题：
《A Survey on Hardware Implementations of Visual Object Trackers》
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作者：
Al-Hussein A. El-Shafie and S. E. D. Habib
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最新提交年份：
2017
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分类信息：
一级分类：Electrical Engineering and Systems Science 电气工程与系统科学
二级分类：Image and Video Processing 图像和视频处理
分类描述：Theory, algorithms, and architectures for the formation, capture, processing, communication, analysis, and display of images, video, and multidimensional signals in a wide variety of applications. Topics of interest include: mathematical, statistical, and perceptual image and video modeling and representation; linear and nonlinear filtering, de-blurring, enhancement, restoration, and reconstruction from degraded, low-resolution or tomographic data; lossless and lossy compression and coding; segmentation, alignment, and recognition; image rendering, visualization, and printing; computational imaging, including ultrasound, tomographic and magnetic resonance imaging; and image and video analysis, synthesis, storage, search and retrieval.
用于图像、视频和多维信号的形成、捕获、处理、通信、分析和显示的理论、算法和体系结构。感兴趣的主题包括：数学，统计，和感知图像和视频建模和表示；线性和非线性滤波、去模糊、增强、恢复和重建退化、低分辨率或层析数据；无损和有损压缩编码；分割、对齐和识别；图像渲染、可视化和打印；计算成像，包括超声、断层和磁共振成像；以及图像和视频的分析、合成、存储、搜索和检索。
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一级分类：Computer Science 计算机科学
二级分类：Computer Vision and Pattern Recognition 计算机视觉与模式识别
分类描述：Covers image processing, computer vision, pattern recognition, and scene understanding. Roughly includes material in ACM Subject Classes I.2.10, I.4, and I.5.
涵盖图像处理、计算机视觉、模式识别和场景理解。大致包括ACM课程I.2.10、I.4和I.5中的材料。
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英文摘要：
Visual object tracking is an active topic in the computer vision domain with applications extending over numerous fields. The main sub-tasks required to build an object tracker (e.g. object detection, feature extraction and object tracking) are computation-intensive. In addition, real-time operation of the tracker is indispensable for almost all of its applications. Therefore, complete hardware or hardware/software co-design approaches are pursued for better tracker implementations. This paper presents a literature survey of the hardware implementations of object trackers over the last two decades. Although several tracking surveys exist in literature, a survey addressing the hardware implementations of the different trackers is missing. We believe this survey would fill the gap and complete the picture with the existing surveys of how to design an efficient tracker and point out the future directions researchers can follow in this field. We highlight the lack of hardware implementations for state-of-the-art tracking algorithms as well as for enhanced classical algorithms. We also stress the need for measuring the tracking performance of the hardware-based trackers. Additionally, enough details of the hardware-based trackers need to be provided to allow reasonable comparison between the different implementations.
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PDF链接：
https://arxiv.org/pdf/1711.02441
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