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Feature-aided multiple hypothesis tracking using topological and statistical behavior classifiers

Publication ,  Conference
Rouse, D; Watkins, A; Porter, D; Harer, J; Bendich, P; Strawn, N; Munch, E; Desena, J; Clarke, J; Gilbert, J; Chin, S; Newman, A
Published in: Proceedings of SPIE - The International Society for Optical Engineering
January 1, 2015

This paper introduces a method to integrate target behavior into the multiple hypothesis tracker (MHT) likelihood ratio. In particular, a periodic track appraisal based on behavior is introduced that uses elementary topological data analysis coupled with basic machine learning techniques. The track appraisal adjusts the traditional kinematic data association likelihood (i.e., track score) using an established formulation for classification-aided data association. The proposed method is tested and demonstrated on synthetic vehicular data representing an urban traffic scene generated by the Simulation of Urban Mobility package. The vehicles in the scene exhibit different driving behaviors. The proposed method distinguishes those behaviors and shows improved data association decisions relative to a conventional, kinematic MHT.

Duke Scholars

Published In

Proceedings of SPIE - The International Society for Optical Engineering

DOI

EISSN

1996-756X

ISSN

0277-786X

ISBN

9781628415902

Publication Date

January 1, 2015

Volume

9474

Related Subject Headings

  • 5102 Atomic, molecular and optical physics
  • 4009 Electronics, sensors and digital hardware
  • 4006 Communications engineering
 

Citation

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Rouse, D., Watkins, A., Porter, D., Harer, J., Bendich, P., Strawn, N., … Newman, A. (2015). Feature-aided multiple hypothesis tracking using topological and statistical behavior classifiers. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 9474). https://doi.org/10.1117/12.2179555
Rouse, D., A. Watkins, D. Porter, J. Harer, P. Bendich, N. Strawn, E. Munch, et al. “Feature-aided multiple hypothesis tracking using topological and statistical behavior classifiers.” In Proceedings of SPIE - The International Society for Optical Engineering, Vol. 9474, 2015. https://doi.org/10.1117/12.2179555.
Rouse D, Watkins A, Porter D, Harer J, Bendich P, Strawn N, et al. Feature-aided multiple hypothesis tracking using topological and statistical behavior classifiers. In: Proceedings of SPIE - The International Society for Optical Engineering. 2015.
Rouse, D., et al. “Feature-aided multiple hypothesis tracking using topological and statistical behavior classifiers.” Proceedings of SPIE - The International Society for Optical Engineering, vol. 9474, 2015. Scopus, doi:10.1117/12.2179555.
Rouse D, Watkins A, Porter D, Harer J, Bendich P, Strawn N, Munch E, Desena J, Clarke J, Gilbert J, Chin S, Newman A. Feature-aided multiple hypothesis tracking using topological and statistical behavior classifiers. Proceedings of SPIE - The International Society for Optical Engineering. 2015.
Journal cover image

Published In

Proceedings of SPIE - The International Society for Optical Engineering

DOI

EISSN

1996-756X

ISSN

0277-786X

ISBN

9781628415902

Publication Date

January 1, 2015

Volume

9474

Related Subject Headings

  • 5102 Atomic, molecular and optical physics
  • 4009 Electronics, sensors and digital hardware
  • 4006 Communications engineering