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一种智能手机上的场景实时识别算法

桂振文 陈靖 刘越 王涌天

桂振文, 陈靖, 刘越, 王涌天. 一种智能手机上的场景实时识别算法. 自动化学报, 2014, 40(1): 83-91. doi: 10.3724/SP.J.1004.2014.00083
引用本文: 桂振文, 陈靖, 刘越, 王涌天. 一种智能手机上的场景实时识别算法. 自动化学报, 2014, 40(1): 83-91. doi: 10.3724/SP.J.1004.2014.00083
GUI Zhen-Wen, CHEN Jing, LIU Yue, WANG Yong-Tian. A Real-time Recognition Algorithm of Scenes on Smartphones. ACTA AUTOMATICA SINICA, 2014, 40(1): 83-91. doi: 10.3724/SP.J.1004.2014.00083
Citation: GUI Zhen-Wen, CHEN Jing, LIU Yue, WANG Yong-Tian. A Real-time Recognition Algorithm of Scenes on Smartphones. ACTA AUTOMATICA SINICA, 2014, 40(1): 83-91. doi: 10.3724/SP.J.1004.2014.00083

一种智能手机上的场景实时识别算法

doi: 10.3724/SP.J.1004.2014.00083
基金项目: 

国家高技术研究发展计划(863计划)(2013AA013802);国家自然科学基金(61072096);国家科技重大专项基金(2012ZX03002004)资助

详细信息
    作者简介:

    桂振文 北京理工大学计算机学院博士研究生. 主要研究方向为计算机视觉,图像处理和移动增强现实.E-mail:quizhenwen1983@bit.edu.cn

A Real-time Recognition Algorithm of Scenes on Smartphones

Funds: 

Supported by National High Technology Research and Development Program of China (863 Program) (2013AA013802), National Natural Science Foundation of China (61072096), and National Science and Technology Major Project of China (2012ZX0 3002004)

  • 摘要: 目前常用的SIFT和SURF识别算法存在匹配时间长、运算量大和内存占用多等问题,无法满足实时移动检索应用. 针对这些问题,本文提出了一种智能手机上的实时识别算法,通过缩短特征点检测时间和降低尺度空间特征点定位的复杂度,保证识别的实时性和准确性.实验结果表明,本算法能有效地运行在普通的资源受限智能手机上,具有较好的通用性;同时能实现对场景的实时识别,消耗内存资源也较少,适合在实际应用中使用.
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出版历程
  • 收稿日期:  2012-07-09
  • 修回日期:  2013-03-19
  • 刊出日期:  2014-01-20

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