ANN ensemble online learning strategy in 3d object cognition and recognition based on similarity

  • Authors:

  • Rui Nian;Guangrong Ji;Wencang Zhao;Chen Feng

  • Affiliations:

  • College of Information Science and Engineering, Ocean University of China, China;College of Information Science and Engineering, Ocean University of China, China;College of Information Science and Engineering, Ocean University of China, China;College of Information Science and Engineering, Ocean University of China, China

  • Venue:
  • ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
  • Year:
  • 2005

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Abstract

In this paper, in aid of ANN ensemble, a supervised online learning strategy continuously achieves omnidirectional information accumulation for 3D object cognition from 2D view sequence. The notion of similarity is introduced to solve the paradox between information simplicity and accuracy. Images are segmented into homogeneous region for training, correspondent to distinct model views characteristic of neighboring generalization. Real-time techniques are adopted to expand knowledge until satisfactory. The insert into joint model views is only needed in case of impartibility. Simulation experiment has achieved encouraging results, and proved the approach effective and feasible.