An Exercise in Vehicle Detection

Abstract

In this paper methods of detecting a vehicle in an image are explored. Digital images are taken from a monocular camera Image processing techniques are then applied to the resulting single frames in order to create the feature vector. Finally the resulting features are used to classify whether there is a car in the image or not using support vector machines. These results are compared to those obtained using a neural network. A discussion on techniques to enhance the feature vector and the results from both types of learning machines will be included.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2001
Accession Number
ADA456969

Entities

People

  • Daniel Hicks
  • Jack Reed
  • Michael Del Rose
  • W. Andrew Jackson

Organizations

  • Tank-automotive and Armaments Command

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Computing System Architectures
  • Data Sets
  • Digital Cameras
  • Digital Images
  • Image Processing
  • Images
  • Information Science
  • Learning Machines
  • Machine Learning
  • Network Architecture
  • Neural Networks
  • Pattern Recognition
  • Quadratic Programming
  • Recognition
  • Supervised Machine Learning

Readers

  • Computer Vision.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks