Human shape recognition using the method of moments and artificial neural networks

Author

Nicolaou, Cbristodoulos A. ; Egbert, Allan L., Jr. ; Lacher, R.C. ; Bassett, Susan I.

Author_Institution

Dept. of Comput. Sci., Florida State Univ., Tallahassee, FL, USA

Volume

5

fYear

1999

fDate

1999

Firstpage

3147

Abstract

The research described in the paper explores the feasibility of an automated adaptive system capable of recognizing that a moving object in a sequence of two-dimensional images is a human or, at the very least has a human shape. To address this problem a method employing the method of standard moments, and artificial neural networks has been designed and implemented The results of the method implementation and testing indicate the validity of the system design and the techniques used. The automated human recognition system developed recognizes left and right human profiles with a success rate of 87.5% and 92.5% respectively. The system is also successful in distinguishing images of human profiles from images of tailgating persons, crouching persons, objects, persons with objects and plain image noise

Keywords

backpropagation; feedforward neural nets; image recognition; image sequences; method of moments; multilayer perceptrons; object recognition; self-organising feature maps; unsupervised learning; artificial neural networks; automated adaptive system; crouching persons; human shape recognition; left human profile; method of moments; plain image noise; right human profile; tailgating persons; two-dimensional images; Adaptive systems; Artificial neural networks; Computer science; Design methodology; Humans; Image recognition; Image segmentation; Moment methods; Shape; System testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1999. IJCNN '99. International Joint Conference on

Conference_Location

Washington, DC

ISSN

1098-7576

Print_ISBN

0-7803-5529-6

Type

conf

DOI

10.1109/IJCNN.1999.836155

Filename

836155