Detection and Tracking of Lane Crossing Vehicles in Traffic Video for Abnormality Analysis
Arun Kumar H D1, Prabhakar C J2
1Arun Kumar H D*, Lecturer, Department of Computer Science and MCA, Kuvempu University, Karnataka, India.
2Prabhakar C J, Associate Professor, Department of Computer Science and M.C.A, Kuvempu University, Karnataka, India.
Manuscript received on January 05, 2021. | Revised Manuscript received on March 30, 2021. | Manuscript published on April 30, 2021. | PP: 1-9 | Volume-10 Issue-4, April 2021. | Retrieval Number: 100.1/ijeat.C21410210321 | DOI: 10.35940/ijeat.C2141.0410421
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, we present a novel approach for detection and tracking of lane crossing/illegal lane crossing vehicles in traffic video of urban highways. For that intention, an initial pace is performed that estimates the road region of the geometrical structure. After finding the road region, every vehicle is tracked in order to detect lane crossing vehicles according to the distance between lane lines and vehicle centre, it is followed by tracking of lane crossing vehicles based on model-based strategy. The proposed system has been evaluated using recall and precision metric, which are received using experiments carried on selected video sequences of GRAM-RTM dataset and publically available video sequences. The experimental results present that our method reaches the highest accuracy for detection of vehicles and tracking of lane crossing vehicles.
Keywords: Illegal Lane Crossing, Abnormal Events, Lane Line Detection, Background Detection.
Scope of the Article: Network traffic characterization and measurements