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- W2361537573 abstract "This paper puts forward a novel infrared vehicle detection algorithm with Gabor filter and Support Vector Machines (SVM) classifier here. It consists of two main steps: driven hypothesis generation and hypothesis verification. In the hypothesis generation step, possible image locations where vehicles might be present are hypothesized by pixel-dependent threshold selection and edge detection. Hypothesis verification verifies those hypothesis using Gabor filter for feature extraction and SVM for classification. A feature weighting technique is proposed, that is, the extracted features are weighted according to their neighboring features degree of dispersion. This method is tested under four different videos, illustrating good performance." @default.
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- W2361537573 title "Infrared Vehicle Detection with Gabor Filter and SVM Classifier" @default.
- W2361537573 hasPublicationYear "2005" @default.
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