Title page for ETD etd-06102012-040611

Type of Document Master's Thesis
Author Paripati, Praveen Kumar
URN etd-06102012-040611
Title Polyhedra:representation and recognition
Degree Master of Science
Department Computer Science and Applications
Advisory Committee
Advisor Name Title
Roach, John W. Committee Chair
Bixler, J. Patrick Committee Member
Ehrich, Roger W. Committee Member
Heath, Lenwood S. Committee Member
  • Polyhedra
Date of Defense 1989-05-15
Availability restricted
Computer Aided Design systems intended for three dimensional solid modelling

have traditionally used geometric representations incompatible with established representations

in computer vision. The utilization of object models built using these

systems require a representation conversion before they can be used in automatic

sensing systems. Considerable advantages follow from building a combined CAD

and sensing system based on a common geometric model. For example, a library

of objects can be built up and its models used in vision and touch sensing system

integrated into an automated assembly line to 'discriminate between objects and determine-

orientation and distance. This thesis studies a representation scheme, the

dual spherical representation, useful in geometric modelling and machine recognition.

We prove that the representation uniquely represents genus 0 polyhedra. We

show by,example that our representation is not a strict dual of the vertex connectivity graph, and hence is not necessarily ambiguous. However, we have not been able to prove that the representation is unambiguous. An augmented dual spherical

representation which is unique for general polyhedra is presented. This graph theoretic

approach to polyhedra also results in an elegant method for decomposition of polyhedra into combinatorially convex parts. An algorithm implementation details and experimental results for recognition of polyhedra using a large field tactile

sensor are given. A theorem relating the edges in the dual spherical representation and the edge under perspective projection is proved. Sensor fusion using visual and tactile sensory inputs is proposed to improve recognition rates.

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