Dynamic obstacle identification based on global and local features for a driver assistance system |
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Authors: | Jeong-Woo Woo Young-Chul Lim Minho Lee |
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Affiliation: | (1) School of Electrical Engineering and Computer Science, Kyungpook National University, 1370 Sankyuk-Dong, Puk-Gu, Taegu, 702-701, Korea;(2) Division of Advanced Industrial Science and Technology, Daegu Gyeongbuk Institute of Science and Technology, 711 Hosan-Dong, Dalseo-Gu, Taegu, 704-230, Korea |
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Abstract: | This paper proposes a novel dynamic obstacle recognition system combining global feature with local feature to identify vehicles,
pedestrians and unknown backgrounds for a driver assistance system. The proposed system consists of two main procedures: a
dynamic obstacle detection model to localize an area containing a moving obstacle, and an obstacle identification model, which
is a hybrid of global and local information, for recognizing an obstacle with and without occlusion. A dynamic saliency map
is used for localizing an area containing a moving obstacle. For the global feature analysis, we propose a modified GIST using
orientation features with MAX pooling, which is robust to translation and size variations of an object. Although the global
features are a compact way to represent an object and provide a good accuracy for non-occluded objects, they are sensitive
to image translation and occlusion. Thus, a local feature-based identification model is also proposed and combined with the
global feature. As such, for the obstacle identification problem, the proposed system mainly follows the global feature-based
object identification. If the global feature-based model identifies a candidate area as background, the system verifies the
area again using the local feature-based model. As a result, the proposed system is able to provide information on both the
appearance of obstacles and the class of an obstacle. Experimental results show that the proposed model can successfully detect
obstacle candidates and robustly identify obstacles with and without occlusion. |
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Keywords: | |
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