Graph Matching based Hand Posture Recognition using Neuro-Biologically Inspired Features

被引：0

作者：

Kumar, Pramod P. ^{[1
]}

Vadakkepat, Prahlad ^{[1
]}

Poh, Loh Ai ^{[1
]}

机构：

[1] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117576, Singapore

来源：

11TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV 2010) | 2010年

关键词：

Hand posture recognition; graph matching; human-computer interaction; biologically inspired features; pattern recognition; GESTURE RECOGNITION; OBJECT RECOGNITION; SYSTEM; TRAJECTORIES; EXTRACTION;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

An elastic graph matching algorithm using biologically inspired features is proposed for the recognition of hand postures. Each node in the graph is labeled using an image feature extracted using the computational model of the ventral stream of visual cortex. The graph nodes are assigned to geometrically significant positions in the hand image, and, the model graphs are created. Bunch graph method is used for modeling the variability in hand posture appearance. Recognition of a hand posture is done by the elastic graph matching between the model graphs and the input image. A radial basis function is used as the similarity function for the matching process. The proposed algorithm is tested on a 10 class hand posture database which consists of 478 grey scale images with light and dark backgrounds. The algorithm provided better recognition accuracy (96.35%) compared to the reported results (93.77%) in the literature.

引用

页码：1151 / 1156

页数：6

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