首页    期刊浏览 2022年08月12日 星期五
登录注册

文章基本信息

  • 标题:Discriminative collaborative representation for multimodal image classification
  • 作者:Dawei Sun ; Shicheng Wang ; Dongfang Yang
  • 期刊名称:International Journal of Advanced Robotic Systems
  • 印刷版ISSN:1729-8806
  • 电子版ISSN:1729-8814
  • 出版年度:2017
  • 卷号:14
  • 期号:3
  • DOI:10.1177/1729881417714211
  • 语种:English
  • 出版社:SAGE Publications
  • 摘要:Sparse representation has been widely researched for image-based classification. However, sparse representation classification directly treats training samples as a dictionary, so it needs a large training set and is time consuming, especially for a large training set. To derive a small dictionary, many dictionary learning algorithms are researched. Thus, object recognition problem is transformed to optimize the sparse representation errors on the compact dictionary. The sparse representation optimization is constraint by l 0 -norm, which is NP-hard problem. Though we can use l 1 -norm minimization instead to work effectively, it is still time consuming for optimization. To make the algorithm discriminative and simultaneously decrease the computational burden, we proposed a fast discriminative collaborative representation–based classification algorithm. The new algorithm incorporated the within-class scatter and the linear classification error terms into the objective function to derive a more discriminative dictionary and simultaneously added collaborative representation mechanism to cut off the time consuming. At the end of this article, we designed two experiments to validate our method using near-infrared and AR visible databases for multimodal face recognition. The results showed that our algorithm outperformance sparse representation–based, collaborative representation–based, and discriminative-KSVD classification algorithms.
  • 关键词:Object recognition and classification; collaborative representation; sparse representation; sparse coding; multimodal image
Loading...
联系我们|关于我们|网站声明
国家哲学社会科学文献中心版权所有