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Semantic Geometric Features: A Preliminary Investigation of Automobile Identification

Semantic Geometric Features: A Preliminary Investigation of Automobile Identification. Carl E. Abrams Sung-Hyuk Cha, Michael Gargano, and Charles Tappert. Agenda. Overview of the Problem The Experiments Results Going Forward. Overview. Object recognition remains a hard problem

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Semantic Geometric Features: A Preliminary Investigation of Automobile Identification

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  1. Semantic Geometric Features: A Preliminary Investigation of Automobile Identification Carl E. Abrams Sung-Hyuk Cha, Michael Gargano, and Charles Tappert Pace DPS

  2. Agenda • Overview of the Problem • The Experiments • Results • Going Forward Pace DPS

  3. 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? Pace DPS

  4. 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 Pace DPS

  5. The Vehicles Pace DPS

  6. Experiments used Euclidean Distance as the Measure the xi and ti are measurements from two different vehicles Pace DPS

  7. c b a Experiments used Euclidean Distance as the Measure (x2,y2) c = (a2+b2)1/2 (x1,y1) c = ((x1-x2)2+(y1-y2)2)1/2 Pace DPS

  8. Manufacturers SpecificationsFirst Experiment Pace DPS

  9. Boundary Description using RaysSecond Experiment Pace DPS

  10. Semantic FeaturesThird Experiment Pace DPS

  11. 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 Pace DPS

  12. The Results Pace DPS

  13. 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 Pace DPS

  14. Going Forward • Extend techniques to encompass semantic shapes within an object (shape contexts) • Compare the extended semantic methods to existing methods in multiple domains Pace DPS

  15. Going Forward Shape Contexts Pace DPS

  16. 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 Pace DPS

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