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3-D model based vehicle recognition

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2 Author(s)
Prokaj, J. ; Inst. for Robot. & Intell. Syst., Univ. of Southern California, Los Angeles, CA, USA ; Medioni, G.

We present a method for recognizing a vehicle's make and model in a video clip taken from an arbitrary viewpoint. This is an improvement over existing methods which require a front view. In addition, we present a Bayesian approach for establishing accurate correspondences in multiple view geometry. We take a model-based, top-down approach to classify vehicles. First, the vehicle pose is estimated in every frame by calculating its 3-D motion on a plane using a structure from motion algorithm. Then, exemplars from a database of 3-D models are rotated to the same pose as the vehicle in the video, and projected to the image. Features in the model images and the vehicle image are matched, and a model matching score is computed. The model with the best score is identified as the model of the vehicle in the video. Results on real video sequences are presented.

Published in:

Applications of Computer Vision (WACV), 2009 Workshop on

Date of Conference:

7-8 Dec. 2009