Semantic Geometric Features: A Preliminary Investigation of Automobile Identification

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Semantic Geometric Features A Preliminary
Investigation of Automobile Identification

• Carl E. Abrams
• Sung-Hyuk Cha, Michael Gargano, and Charles
  Tappert

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Agenda

• Overview of the Problem
• The Experiments
• Results
• Going Forward

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Overview

• Object recognition remains a hard problem
• The human mind uses shapes to recognize objects
• Can semantic features defined by their shapes be
  more effective in the recognition and
  identification of objects?

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The Experiments

• 10 test images of cars
• Directly form the manufactures websites
• Images were restricted to side views of the cars
  taken from 90 degrees
• All 2005 models
• Feature vectors calculated/measured from the
  images

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The Vehicles
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Experiments used Euclidean Distance as the
Measure
the xi and ti are measurements from two different
vehicles
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Experiments used Euclidean Distance as the
Measure
(x2,y2)
c (a2b2)1/2
(x1,y1)
c ((x1-x2)2(y1-y2)2)1/2
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Manufacturers SpecificationsFirst Experiment
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Boundary Description using RaysSecond Experiment
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Semantic FeaturesThird Experiment
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Challenge Determine the qualitative ability of
the feature vectors to separate the vehicles

• Within each experiment compute the distance of
  each vehicle from all the others
• Evenly divide the measures into 5 bins
• Observe the distribution of the measures

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The Results
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Distance Matrix Semantic Features
Honda Civic
Honda Accord
Mazda 3
Mazda 6
Porsche Carerra
Toyota Camry
Toyota Celica
Toyota Corolla
Toyota Echo
VW Passat
Honda Civic
Honda Accord
Mazda 3
Mazda 6
Porsche Carerra
Toyota Camry
Toyota Celica
Toyota Corolla
Toyota Echo
VW Passat
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Going Forward

• Extend techniques to encompass semantic shapes
  within an object (shape contexts)
• Compare the extended semantic methods to existing
  methods in multiple domains

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Going Forward
Shape Contexts
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References

• 1 R. D. Acqua and R. Job, "Is global shape
  sufficient for automatic object identification?"
  Congitive Science, vol. 8, pp. 801-821, 2001.
• 2 A. K. Jain, A. Ross, and S. Pankanti, "A
  Prototype Hand Geomtery-based Verification
  System," presented at Proceedings of 2nd
  International conference on Audio and Video-based
  Biometric Person Authentication, Wahington D.C.,
  1999.
• 3 H. Schneiderman and T. Kanade, "A Statistical
  Model for 3D Object Detection Applied to Faces
  and Cars," presented at IEEE Conference on
  Computer Vision and Pattern Recognition, IEEE,
  2000
• 4 S. Belongie,J Malik, J Puzicha, Matching
  Shapes ,presented at the International
  Conference on Computer Vision (ICCV 01) Vol 1,
  Jan 2001