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Vehicle Detection: A Review
Author(s) -
Chaochao Meng,
Hong Bao,
Yan Ma
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1634/1/012107
Subject(s) - computer science , computer vision , artificial intelligence , perception , feature extraction , position (finance) , feature (linguistics) , linguistics , philosophy , finance , neuroscience , economics , biology
Vehicle detection based computer vision is the essential algorithm in autonomous driving, aims at identifying which locating vehicles by digital images or videos. The basic idea of vehicle detection is detecting “blocks,” which reflects the position of the vehicle in images or videos. Besides, this paper discusses 3D vehicle detection algorithms based on stereo perception, which originated from advanced planar vehicle detection perception. Finally, this paper summarizes the vehicle detection algorithms in recent years in terms of the difference between the feature extraction approach and the perceived results. It proposes hypotheses for further in-depth study of the vehicle detection algorithms.

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