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Improving the visibility of nighttime images for pedestrian recognition using in‐vehicle camera
Author(s) -
Ogura Ryota,
Nagasaki Takeshi,
Matsubara Hitoshi
Publication year - 2020
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.12268
Subject(s) - artificial intelligence , computer vision , computer science , visibility , feature extraction , convolution (computer science) , pedestrian , object detection , cognitive neuroscience of visual object recognition , feature (linguistics) , reduction (mathematics) , pattern recognition (psychology) , artificial neural network , engineering , mathematics , geography , linguistics , philosophy , geometry , meteorology , transport engineering
There is a need for methods to recognize night pedestrian to reduce pedestrian traffic accidents at night. In this paper, we proposed the method that converts images using continuous nighttime images from in‐vehicle camera. The proposed method performs feature extraction that does not depend on one's own vehicle speed because inputting continuous nighttime images, and the function of convolution layer that performs dimensionality reduction. In order to confirm the effectiveness of the proposed method, we prepared the images of simulation and camera. The nighttime images were conversed with the proposed method. After conversion, we calculated the recognition performance by applying object detection which is an object recognition method. We showed the proposed method is more robust against the own vehicle speed change.