Traffic intensity monitoring using multiple object detection with traffic surveillance cameras
Object detection and tracking is a field of research that has many applications in the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT). In this paper, a traffic intensity monitoring system is implemented based on the Macroscopic Urban...
| Main Authors: | , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
IOP Publishing
2017
|
| Subjects: | |
| Online Access: | http://irep.iium.edu.my/59584/ http://irep.iium.edu.my/59584/ http://irep.iium.edu.my/59584/ http://irep.iium.edu.my/59584/1/Traffic%20intensity%20monitoring%20using%20multiple%20object%20Muhammad_Hamdan_2017_IOP_Conf._Ser.%253A_Mater._Sci._Eng._260_012009.pdf http://irep.iium.edu.my/59584/12/59584%20Traffic%20intensity%20monitoring%20using%20multiple%20object%20detection%20SCOPUS.pdf |
| Summary: | Object detection and tracking is a field of research that has many applications in the
current generation with increasing number of cameras on the streets and lower cost for Internet
of Things(IoT). In this paper, a traffic intensity monitoring system is implemented based on the
Macroscopic Urban Traffic model is proposed using computer vision as its source. The input of
this program is extracted from a traffic surveillance camera which has another program running
a neural network classification which can identify and differentiate the vehicle type is
implanted. The neural network toolbox is trained with positive and negative input to increase
accuracy. The accuracy of the program is compared to other related works done and the trends
of the traffic intensity from a road is also calculated. relevant articles in literature searches,
great care should be taken in constructing both. Lastly the limitation and the future work is
concluded. |
|---|