A Simple Approach for Real Time Speed Estimation of On Road Vehicles Using Video Sequences
Publish place: Third National Conference and First International Conference on Applied Research in Electrical, Mechanical and Mechatronics Engineering
Publish Year: 1394
Type: Conference paper
Language: English
View: 757
This Paper With 7 Page And PDF Format Ready To Download
- Certificate
- I'm the author of the paper
Export:
Document National Code:
ELEMECHCONF03_0083
Index date: 30 July 2016
A Simple Approach for Real Time Speed Estimation of On Road Vehicles Using Video Sequences abstract
This paper provides an efficient and simple approach towards real-time speed estimation of on road vehicles for surveillance applications. In the presented method, videos are supposed to be captured with a stationary camera mounted on a two-lane road and there is no need for the camera to be calibrated. The algorithm has two main phases, in the first phase there is an interactive procedure in which lane borders and real world distances are defined just once at the beginning. Then, based on the already received information, two rectangular ROIs are defined for each lane. In the second phase, approximate binary mask of the foreground is created differencing the two consecutive frames. Eventually, calculating centroids and the norm values of the binary mask in the ROIs, algorithm can compute the time that it takes each vehicle to pass between the two aforementioned lines and thus, average speed can be computed. In short, although the algorithm of this paper is simple, it is real-time and fficient, and its implementation doesn’t require any specific hardware. The average error of speed estimation is ±3km/h and the detection accuracy is 83 %.
A Simple Approach for Real Time Speed Estimation of On Road Vehicles Using Video Sequences Keywords:
A Simple Approach for Real Time Speed Estimation of On Road Vehicles Using Video Sequences authors
Ahmad Mosayebi
Electrical Engineering Department, Shahrood University
Hossein Khosravi
Electrical Engineering Department, Shahrood University
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :