On road vehicle make and model recognition via sparse feature coding

Automatic vehicle Make and Model Recognition (MMR) system offers a competent way to vehicle classification and recognition systems. This paper proposes a real time while robust vehicle make and model recognition system extracting the vehicle sub-image from the background and studies some sparse feat...

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Bibliographic Details
Main Authors: Nazemi, A., Shafiee, M. J., Azimifar, Z.
Format: Conference Proceeding
Language:English
Subjects:
bag of words
Computer vision
Dictionaries
Encoding
Feature extraction
hard vector quantization
Image coding
Kernel
make and model recognition
orthogonal matching pursuit
sparse coding
Vehicles
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Summary:Automatic vehicle Make and Model Recognition (MMR) system offers a competent way to vehicle classification and recognition systems. This paper proposes a real time while robust vehicle make and model recognition system extracting the vehicle sub-image from the background and studies some sparse feature coding methods such as Orthogonal Matching Pursuit (OMP), some variation of Sparse Coding (SC) methods and compares them to choose the best one. Our method employs the sparse feature coding methods on dense Scale-Invariant Feature Transform (SIFT) features and Support Vector Machine (SVM) for classification. The proposed system is examined by an Iranian on road vehicles dataset, which its samples are in different point of views, various weather conditions and illuminations.
ISSN:2166-6776
DOI:10.1109/IranianMVIP.2013.6780025