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Overview of approaches for accelerating scale invariant feature detection algorithm

机译:加速尺度不变特征检测算法的方法概述

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摘要

SIFT (Scale Invariant Feature Transform) is one of most popular approach for feature detection and matching. Many parallelized algorithms have been proposed to accelerate SIFT to apply into real-time systems. This paper divides the researches into three different categories, that is, optimizing parallel algorithms based on general purpose multi-core processors, designing customized multi-core processor dedicated for SIFT and implementing SIFT based FPGA (Field Programmable Gate Arrays). Overview of the three type researches and analysis of task-level parallelism are presented in this paper.
机译:SIFT(尺度不变特征变换)是用于特征检测和匹配的最受欢迎的方法之一。已经提出了许多并行算法来加速SIFT应用于实时系统。本文将研究分为三个不同的类别,即基于通用多核处理器优化并行算法,设计专用于SIFT的定制多核处理器以及实现基于SIFT的FPGA(现场可编程门阵列)。本文对这三种类型的研究进行了概述,并对任务级并行性进行了分析。

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