Object segmentation using maximum neural networks for the gesture recognition system

Noriko Yoshiike; Yoshiyasu Takefuji

doi:10.1016/S0925-2312(02)00617-3

Object segmentation using maximum neural networks for the gesture recognition system

Noriko Yoshiike, Yoshiyasu Takefuji

Faculty of Environment and Information Studies

Research output: Contribution to journal › Article › peer-review

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 language	English
Pages (from-to)	213-224
Number of pages	12
Journal	Neurocomputing
Volume	51
DOIs	https://doi.org/10.1016/S0925-2312(02)00617-3
Publication status	Published - 2003 Apr 1

Keywords

Gesture recognition
Maximum neural networks
Object segmentation

ASJC Scopus subject areas

Computer Science Applications
Cognitive Neuroscience
Artificial Intelligence

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10.1016/S0925-2312(02)00617-3

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keywords = "Gesture recognition, Maximum neural networks, Object segmentation",

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AU - Takefuji, Yoshiyasu

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AB - 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.

KW - Gesture recognition

KW - Maximum neural networks

KW - Object segmentation

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JO - Neurocomputing

JF - Neurocomputing

SN - 0925-2312

ER -

Object segmentation using maximum neural networks for the gesture recognition system

Abstract

Keywords

ASJC Scopus subject areas

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