Integration of Multiple Cues for Robust 3D Object Description: A Computational and Psychophysical Study with Applications

Abstract

The project involves a comprehensive study of object description using multi-sensors. The study examines two basic scenarios for surface reconstruction. The first scenario provides a 2D - to - 3D mapping from images to surfaces and will indude stereo, focus, zoom, vergence, shape from shading, and shape from texture. The second scenario uses active range finders to provide direct depth information about the object, i.e., provides a 3D - to - 3D mapping. The research focuses on the representation and fusion of information form differing image sources and the use of machine learning techniques to perform the fusion. Psychophysical studies conducted include investigating the applicability of the recently introduced" quasi 2D coding hypothesis for 3D surface representation" in machine vision; and the behavioral evaluation of human performance with 3D fused imagery. The investigations of 3D surface reconstruction in human, computer and robot vision have an important applications in military, manufacturing and medical areas. As described in technical report this research has been conducted in the Computer Vision and Image Processing Laboratory (CVIP Lab) at the University of Louisville. The "vision environment" created in the CVIP Lab enabled integration of multiple cues to sense, explore and reconstruct the environment layout. As a result, an active vision system called the CardEye was created.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2001
Accession Number
ADA395273

Entities

People

  • Aly A. Farag

Organizations

  • University of Louisville

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Artificial Intelligence
  • Computer Stereo Vision
  • Computer Vision
  • Computers
  • Coordinate Systems
  • Differential Equations
  • Image Processing
  • Image Recognition
  • Joints (Anatomy)
  • Machine Perception
  • Mechanical Properties
  • Object Recognition
  • Recognition
  • Three Dimensional
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Research Science/Academic Research
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML
  • Autonomy