Evaluation of the Approach for the Identification of Trajectory Anomalies on CCTV Video from Road Intersections

Rifkat Minnikhanov, Igor Anikin, Aigul Mardanova, Maria Dagaeva, Alisa Makhmutova and Azat Kadyrov
Additional contact information
Rifkat Minnikhanov: Road Safety State Company, 420059 Kazan, Russia
Igor Anikin: Information Security Systems Department, Kazan National Research Technical University Named after A.N. Tupolev-KAI, 420111 Kazan, Russia
Aigul Mardanova: Zalando Logistics SE & Co. KG, 99098 Erfurt, Germany
Maria Dagaeva: Road Safety State Company, 420059 Kazan, Russia
Alisa Makhmutova: Information Security Systems Department, Kazan National Research Technical University Named after A.N. Tupolev-KAI, 420111 Kazan, Russia
Azat Kadyrov: Road Safety State Company, 420059 Kazan, Russia

Mathematics, 2022, vol. 10, issue 3, 1-20

Abstract: The approach for the detection of vehicle trajectory abnormalities on CCTV video from road intersections was proposed and evaluated. We mainly focused on the trajectory analysis method rather than objects detection and tracking. Two basic challenges have been overcome in the suggested approach—spatial perspective on the image and performance. We used trajectory approximation by polynomials as well as the Ramer-Douglas-Peucker N thinning technique to increase the performance of the trajectory comparison method. Special modification of trajectory similarity metric LCSS was suggested to consider the spatial perspective. We used clustering to discover two types of classes—with normal and abnormal trajectories. The framework, which implements the suggested approach, was developed. A series of experiments were carried out for testing the approach and defining recommendations for using different techniques in the scope of it.

Keywords: intelligent transport systems; video processing; trajectories; clustering; anomaly detection (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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