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標題Title: BRIEF: Computing a Local Binary Descriptor Very Fast
作者Authors: 徐苡庭,陳昶安..等
上傳單位Department: 資訊工程系
上傳時間Date: 2013-12-30
上傳者Author: 徐苡庭
審核單位Department: 資訊工程系
審核老師Teacher: 李南逸
檔案類型Categories: 課堂報告In-class Report
關鍵詞Keyword: Index Terms—Image processing and computer vision, feature matching, augmented reality, real-time matching.
摘要Abstract: Abstract—Binary descriptors are becoming increasingly popular as a means to compare feature points very fast while requiring
comparatively small amounts of memory. The typical approach to creating them is to first compute floating-point ones, using an
algorithm such as SIFT, and then to binarize them. In this paper, we show that we can directly compute a binary descriptor, which we
call BRIEF, on the basis of simple intensity difference tests. As a result, BRIEF is very fast both to build and to match. We compare it
against SURF and SIFT on standard benchmarks and show that it yields comparable recognition accuracy, while running in an almost
vanishing fraction of the time required by either.

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2013_12_ece27d67.pdf 989Kb pdf 82 10
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