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Two-wheeler Detection using the Local Uniform Projection Vector based on Curvature Feature
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 Title & Authors
Two-wheeler Detection using the Local Uniform Projection Vector based on Curvature Feature
Lee, Yeunghak; Kim, Taesun; Shim, Jaechang;
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 Abstract
Recent research has been devoted and focused on detecting pedestrian and vehicle in intelligent vehicles except for the vulnerable road user(VRUS). In this paper suggest a new projection method which has robustness for rotation invariant and reducing dimensionality for each cell from original image to detect two-wheeler. We applied new weighting values which are calculated by maximum curvature containing very important object shape features and uniform local binary pattern to remove the noise. This paper considered the Adaboost algorithm to make a strong classification from weak classification. Experiment results show that the new approach gives higher detection accuracy than of the conventional method.
 Keywords
Two-wheeler;Curvature;Adaboost;Projection;Local Binary Pattern;
 Language
Korean
 Cited by
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