JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
A Tracking-by-Detection System for Pedestrian Tracking Using Deep Learning Technique and Color Information |
| 영문제목(English Title) |
A Tracking-by-Detection System for Pedestrian Tracking Using Deep Learning Technique and Color Information |
| 저자(Author) |
Mai Thanh Nhat Truong
Sanghoon Kim
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| 원문수록처(Citation) |
VOL 15 NO. 04 PP. 1017 ~ 1028 (2019. 08) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Pedestrian tracking is a particular object tracking problem and an important component in various visionbased applications, such as autonomous cars and surveillance systems. Following several years of development, pedestrian tracking in videos remains challenging, owing to the diversity of object appearances and surrounding environments. In this research, we proposed a tracking-by-detection system for pedestrian tracking, which incorporates a convolutional neural network (CNN) and color information. Pedestrians in video frames are localized using a CNN-based algorithm, and then detected pedestrians are assigned to their corresponding tracklets based on similarities between color distributions. The experimental results show that our system is able to overcome various difficulties to produce highly accurate tracking results.
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| 키워드(Keyword) |
Color Distribution
Convolutional Neural Network
Pedestrian Tracking
Tracking-by-Detection
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| 파일첨부 |
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