Title

Enhanced Vehicle Classification Via 3D Geometries

Abstract

We present a mobile vehicle classification technique achieved by tracking two vehicle based Points of Interest (PoI) in multiple filter configurations to compose a vehicle specific 3D geometry. Using high fidelity physics based simulation we demonstrate the capability to classify the 3D geometries in the presence of noise by extracting vector magnitudes and angles as features. Additionally, we investigate the classification advantages presented by representing the features in multiple linear transform domains and fusing the information from those different domains into a single ensemble classifier.

Publication Date

9-27-2017

Publication Title

Midwest Symposium on Circuits and Systems

Volume

2017-August

Number of Pages

1497-1500

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/MWSCAS.2017.8053218

Socpus ID

85034088991 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85034088991

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