DYNAMIC PATTERN-RECOGNITION OF COORDINATED BIOLOGICAL MOTION

被引：30

作者：

HAKEN, H ^{[1
]}

KELSO, JAS ^{[1
]}

FUCHS, A ^{[1
]}

PANDYA, AS ^{[1
]}

机构：

[1] FLORIDA ATLANTIC UNIV,BOCA RATON,FL 33431

来源：

NEURAL NETWORKS | 1990年 / 3卷 / 04期

关键词：

D O I：

10.1016/0893-6080(90)90022-D

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We develop an algorithm that enables the identification and categorization of visually created patterns of coordinated biological motion, specifically, different multijoint limb trajectories produced by humans. The algorithm uses identified collective variables or order parameters as the basis for encoding these patterns, obtained through experimental studies of phase transitions by Kelso and colleagues. Thus, meaningful information for recognizing dynamic visual patterns resides in attractors of the order parameter dynamics. In a neural net, these order parameters represent different macrostates of the net as a whole (rather than the interactions of single neurons), thereby constituting a synergetically organized neural field, in the fashion of a Gestalt-like process. © 1990.

引用

页码：395 / 401

页数：7

共 33 条

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[2]

CUTTING JE, 1981, INTERSENSORY PERCEPT

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