Object segmentation using maximum neural networks for the gesture recognition system

Noriko Yoshiike, Yoshiyasu Takefuji

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

In this paper, we present a new clustering method for segmentations of moving target and non-target objects. We assume that the moving target object has the following conditions: (1) object motion data continuity inter-frame, and (2) object motion data continuity intra-frame. In our model, clusters tend to form as filling these two conditions. The experimental results showed the effectiveness of the proposed algorithm and the performance of this model in terms of the quality of the recognition results. Our algorithm is able to clean the input noise by removing non-target objects before the recognition process.

Original languageEnglish
Pages (from-to)213-224
Number of pages12
JournalNeurocomputing
Volume51
DOIs
Publication statusPublished - 2003 Apr

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Gesture recognition
Gestures
Neural networks
Cluster Analysis

Keywords

  • Gesture recognition
  • Maximum neural networks
  • Object segmentation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Cellular and Molecular Neuroscience

Cite this

Object segmentation using maximum neural networks for the gesture recognition system. / Yoshiike, Noriko; Takefuji, Yoshiyasu.

In: Neurocomputing, Vol. 51, 04.2003, p. 213-224.

Research output: Contribution to journalArticle

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