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ANNPR
2008
Springer

Multi-class Vehicle Type Recognition System

13 years 4 months ago
Multi-class Vehicle Type Recognition System
This paper presents a framework for multiclass vehicle type (Make and Model) identification based on oriented contour points. A method to construct a model from several frontal vehicle images is presented. Employing this model, three voting algorithms and a distance error allows to measure the similarity between an input instance and the data bases classes. These scores could be combined to design a discriminant function. We present too a second classification stage that employ scores like vectors. A nearest-neighbor algorithm is used to determine the vehicle type. This method have been tested on a realistic data set (830 images containing 50 different vehicle classes) obtaining similar results for equivalent recognition frameworks with different features selections [12]. The system also shows to be robust to partial occlusions.
Xavier Clady, Pablo Negri, Maurice Milgram, Raphae
Added 08 Nov 2010
Updated 08 Nov 2010
Type Conference
Year 2008
Where ANNPR
Authors Xavier Clady, Pablo Negri, Maurice Milgram, Raphael Poulenard
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