Abstract
An appearance-based eigenspace method for classifying moving cars is introduced in this paper A car can be classified by observing any of its partial view, using this method. We present a new algorithm called eigendimension matching instead of calculating euclidean distance between eigensubspaces for the identification and classification of moving cars. The proposed method is based on: the establishment of eigenspaces of a set of known car images, and comparing their eigendimensions to classify the unknown car or non-car images. Experimental results from the real-world data show the effectiveness of the proposed method.
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