Electronics Optics & Control, Volume. 29, Issue 3, 110(2022)

ORB Feature Extraction and Tracking Based on Adaptive Threshold

ZONG Zehua1...2, ZHANG Haijun3 and ZHANG Jinfeng3 |Show fewer author(s)
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  • 1[in Chinese]
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  • 3[in Chinese]
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    References(7)

    [1] [1] SEFATI M,DAUM M,SONDERMANN B,et al.Improving vehicle localization using semantic and pole-like landmarks[C]//IEEE Intelligent Vehicles Symposium.Los Angeles:IEEE,2017:13-19.

    [2] [2] YANG L,WANG B Q,ZHANG R H,et al.Analysis on location accuracy for the binocular stereo vision system[J].IEEE Photonics Journal,2018,10(1):316-324.

    [3] [3] FAN B,WU F C,HU Z Y.Rotationally invariant descriptors using intensity order pooling[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2012,34(10):2031-2045.

    [4] [4] CHOI J Y,SUNG K S,YANG Y K.Multiple vehicles detection and tracking based on scale-invariant feature transform[C]//IEEE Intelligent Transportation Systems Conference.Bellevue:IEEE,2007:528-533.

    [5] [5] ZHANG H L,WANG Y F,LUO L K,et al.SIFT flow for abrupt motion tracking via adaptive samples selection with sparse representation[J].Neurocomputing,2017,249(2):253-265.

    [6] [6] RUBLEE E,RABAUD V,KONOLIGE K,et al.ORB:an efficient alternative to SIFT or SURF[C]//IEEE International Conference on Computer Vision.Barcelona:IEEE, 2011: 2564-2571.

    [7] [7] LI J Y,WANG Y L,WANG Y J.Visual tracking and learning using speeded up robust features[J].Pattern Recognition Letters,2012,33(16):2094-2101.

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    ZONG Zehua, ZHANG Haijun, ZHANG Jinfeng. ORB Feature Extraction and Tracking Based on Adaptive Threshold[J]. Electronics Optics & Control, 2022, 29(3): 110

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    Paper Information

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    Received: Nov. 2, 2021

    Accepted: --

    Published Online: Mar. 16, 2022

    The Author Email:

    DOI:10.3969/j.issn.1671-637x.2022.03.022

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