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基于背景属性的目标识别

雒建卫 姜志国

雒建卫, 姜志国. 基于背景属性的目标识别[J]. 北京航空航天大学学报, 2014, 40(12): 1702-1706. doi: 10.13700/j.bh.1001-5965.2013.0750
引用本文: 雒建卫, 姜志国. 基于背景属性的目标识别[J]. 北京航空航天大学学报, 2014, 40(12): 1702-1706. doi: 10.13700/j.bh.1001-5965.2013.0750
Luo Jianwei, Jiang Zhiguo. Object recognition based on background attributes[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(12): 1702-1706. doi: 10.13700/j.bh.1001-5965.2013.0750(in Chinese)
Citation: Luo Jianwei, Jiang Zhiguo. Object recognition based on background attributes[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(12): 1702-1706. doi: 10.13700/j.bh.1001-5965.2013.0750(in Chinese)

基于背景属性的目标识别

doi: 10.13700/j.bh.1001-5965.2013.0750
基金项目: 国家自然科学基金资助项目(61371134);国家973计划资助项目(2010CB327900)
详细信息
    作者简介:

    雒建卫(1986-),男,河南焦作人,博士生,ljw321521@gmail.com.

  • 中图分类号: TP391

Object recognition based on background attributes

  • 摘要: 属性是图像的语义描述,可以表示图像中某些内容的存在与否,它可以是物体的形状、材质、部件、类别以及功能,也可以是场景的类别以及上下文信息等.由于目标类别与所在背景存在相关关系,提出基于背景属性和目标属性相融合的前景目标识别方法,即对每种背景属性和目标属性分别训练支持向量机(SVM)分类器,并将属性在对应分类器上的得分进行串联组成新的特征,并训练得到最终分类器.对a-Pascal数据库中每幅图像,人工标注了10种背景属性,结合已有的目标属性,进行目标识别实验.与传统方法、基于目标属性的分类方法以及其他前景、背景相结合算法的对比实验结果表明,所提算法比其他算法提高大约2%,背景属性有助于提高目标识别率.

     

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出版历程
  • 收稿日期:  2014-01-08
  • 网络出版日期:  2014-12-20

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