Multiresolutional Sensor Fusion By Conductivity Analysis | Zendy

H.E. Stephanou | Zendy; Aydan M. Erkmen | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Multiresolutional Sensor Fusion By Conductivity Analysis

Author(s) -

H.E. Stephanou,

Aydan M. Erkmen

Publication year - 1990

Publication title -

proceedings of spie, the international society for optical engineering/proceedings of spie

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.192

H-Index - 176

eISSN - 1996-756X

pISSN - 0277-786X

DOI - 10.1117/12.969995

Subject(s) - sensor fusion , computer science , artificial intelligence , pattern recognition (psychology) , representation (politics) , classifier (uml) , sensory system , focus (optics) , curvature , measure (data warehouse) , data mining , mathematics , psychology , optics , politics , political science , law , cognitive psychology , physics , geometry

This paper describes an evidential pattern classifier for the combination of data from physically different sensors. We assume that the sensory evidence is multiresolutional, incomplete, imprecise, and possibly inconsistent. Our focus is on two types of sensory information patterns: visual and tactile. We develop a logical sensing scheme by using a model based representation of prototypical 3D surfaces. Each surface represents a class of topological patterns described by shape and curvature features. The sensory evidence is classified by using a conductivity measure to determine which prototypical surface best matches the evidence. A formal evidential model of uncertainty is used to derive logical sensors and provide performance measures for sensor integration algorithms.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research