计算机科学
现场可编程门阵列
实施
预处理器
机器视觉
目标检测
人工智能
领域(数学)
嵌入式系统
视觉对象识别的认知神经科学
计算机体系结构
对象(语法)
模式识别(心理学)
软件工程
数学
纯数学
作者
Deepayan Bhowmik,Kofi Appiah
标识
DOI:10.1007/978-3-319-78890-6_17
摘要
Over the past two decades, the use of low power Field Programmable Gate Arrays (FPGA) for the acceleration of various vision systems mainly on embedded devices have become widespread. The reconfigurable and parallel nature of the FPGA opens up new opportunities to speed-up computationally intensive vision and neural algorithms on embedded and portable devices. This paper presents a comprehensive review of embedded vision algorithms and applications over the past decade. The review will discuss vision based systems and approaches, and how they have been implemented on embedded devices. Topics covered include image acquisition, preprocessing, object detection and tracking, recognition as well as high-level classification. This is followed by an outline of the advantages and disadvantages of the various embedded implementations. Finally, an overview of the challenges in the field and future research trends are presented. This review is expected to serve as a tutorial and reference source for embedded computer vision systems.
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