A Real-time MultispectralAlgorithmforRobusttime Multispectral Algorithm for Robust PedestrianDetectionPedestrian Detection

被引：0
|
作者：
Vu Hiep Dao [1 ]
Hieu Mac [1 ]
Duc Tran [1 ]
机构：
[1] Hanoi Univ Sci & Technol, Sch Informat & Commun Technol, Hanoi, Vietnam
来源：
2021 RIVF INTERNATIONAL CONFERENCE ON COMPUTING AND COMMUNICATION TECHNOLOGIES (RIVF 2021) | 2021年
关键词：
thermal image; pedestrian detection; convolutional neural networks; Yolo;
D O I：
10.1109/RIVF51545.2021.9642066
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Low light conditions are known to create a notable challenge to the applicability of deep learning in a wide variety of computer vision applications. In this paper, we develop a detection method for real-time multispectral pedestrians that fuses color image (i.e., red-green-blue or RBG) with thermal image to provide a reliable object vision. Such combination is achieved using the confidence scores that are computed based on the illumination measure of a given input image. We evaluate the proposed algorithm on KAIST dataset. Such method is observed to give a 34.11% Log Average Miss Rate, operate in real-time, and thus, being ready to deploy in practice.
引用
收藏
页码：61 / 64
页数：4
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