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  • 标题:NOVEL MULTI-CLASS SVM ALGORITHM FOR MULTIPLE OBJECT RECOGNITION
  • 本地全文:下载
  • 作者:Yongqing Wang ; Yanzhou Zhang
  • 期刊名称:International Journal on Smart Sensing and Intelligent Systems
  • 印刷版ISSN:1178-5608
  • 出版年度:2015
  • 卷号:8
  • 期号:2
  • 页码:1203-1224
  • 出版社:Massey University
  • 摘要:Object recognition is a fundamental task in applications of computer vision, which aims at detecting and locating the interested objects out of the backgrounds in images or videos, and can be originally formulated as a binary classification problem that can be effectively handled by binary SVM. Although the binary technique can be naturally extended to solve the multiple object recognition, which are known as one-vs.-one and one-vs.-all techniques, but the scalability of traditional methods tend to be poor, and limits the wide applications. Inspired by the idea presented by Multi-class Core Vector Machine, we propose a novel Multi-class SVM algorithm, which achieves excellent performance on dealing with multiple object recognition. The simulation results on synthetic numerical data and recognition results on real-world pictures demonstrate the validity of the proposed algorithm.
  • 关键词:Object recognition; computer vision; multi-class; SVM algorithm; classification problem
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