TY - GEN
T1 - Four categories vehicle detection in hsuehshan tunnel via single shot multibox detector
AU - Tsai, Chun Ming
AU - Shou, Tawei
AU - Hsieh, Jun-Wei
AU - Chen, Kuang Hsuan
PY - 2019/8
Y1 - 2019/8
N2 - Taiwan has many vehicles and as a result many traffic problems. In particular, during the Spring Festival and the holidays, Hsuehshan Tunnel (HST) between Yilan and Taipei is always a traffic jam. To solve this problem, intelligent transportation system (ITS) is necessary, and accurate vehicle detection (VD) is the first stage for ITS. In order to detect vehicles in HST, three training methods based on single shot multibox detector (SSD) are presented to detect four categories of vehicle in the Tunnel. The experimental results demonstrated that the presented three training methods, which only used 1000 training frames, can detect and categorize more vehicles than the pre-trained SSD model which used a large training dataset. Specifically, the SSD trained by our collected data set and data augmentation has the highest detection rates for sedan, van, bus, and truck - 93.6%, 90.9%, 100%, and 100%, respectively.
AB - Taiwan has many vehicles and as a result many traffic problems. In particular, during the Spring Festival and the holidays, Hsuehshan Tunnel (HST) between Yilan and Taipei is always a traffic jam. To solve this problem, intelligent transportation system (ITS) is necessary, and accurate vehicle detection (VD) is the first stage for ITS. In order to detect vehicles in HST, three training methods based on single shot multibox detector (SSD) are presented to detect four categories of vehicle in the Tunnel. The experimental results demonstrated that the presented three training methods, which only used 1000 training frames, can detect and categorize more vehicles than the pre-trained SSD model which used a large training dataset. Specifically, the SSD trained by our collected data set and data augmentation has the highest detection rates for sedan, van, bus, and truck - 93.6%, 90.9%, 100%, and 100%, respectively.
KW - Deep learning
KW - Four categories vehicle detection
KW - Hsuehshan Tunnel
KW - Intelligent transportation system
KW - Single shot multibox detector
UR - http://www.scopus.com/inward/record.url?scp=85083425825&partnerID=8YFLogxK
U2 - 10.1109/Ubi-Media.2019.00030
DO - 10.1109/Ubi-Media.2019.00030
M3 - Conference contribution
AN - SCOPUS:85083425825
T3 - Proceedings - 2019 12th International Conference on Ubi-Media Computing, Ubi-Media 2019
SP - 113
EP - 118
BT - Proceedings - 2019 12th International Conference on Ubi-Media Computing, Ubi-Media 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th International Conference on Ubi-Media Computing, Ubi-Media 2019
Y2 - 6 August 2019 through 9 August 2019
ER -