Dr. Yafan Zhao Profile

Dr. Yafan Zhao

at Robert Gordon Univ

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Proceedings Article | 17 October 2023 Presentation + Paper

Detecting and tracking the position of suspicious objects using vision system

Ramkumar Muthukrishnan, Somasundar Kannan, Radhakrishna Prabhu, Yafan Zhao, Parijat Bhowmick

Proceedings Volume 12742, 127420C (2023) https://doi.org/10.1117/12.2679801

KEYWORDS: Object detection, Algorithm development, Visual process modeling, RGB color model, Machine learning, Image processing

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Vision-based object tracking is crucial for both civil and military applications. A range of hazards to cyber safety, vital infrastructure, and public privacy are posed by the rise of drones, or unmanned aerial vehicles (UAV). As a result, identifying and tracking suspicious drones/UAV is a serious challenge and that has attracted strong research attention recently. The focus of this research is to develop a new virtual coloured marker based tracking algorithm for estimating the posture of the detected object. After detection, the developed algorithm initiates by determining the coloured area of the detected object as reference-contour. Followed by a Virtual-Bounding Box (V-BB) created over the reference-contour by meeting the minimum area of contour criteria. Additionally, a Virtual Dynamic Crossline with a Virtual Static Graph (VDC-VSG) was developed to track the movement of V-BB, which is considered as virtual coloured marker, helps to estimate the pose of the detected object during observations. Moreover, V-BB helps to avoid ambient illumination-related difficulties during tracking process. A significant number of aerial sequences, including benchmark footage, were tested using the proposed approach, and the outputs were highly encouraging, with satisfactory results. Potential applications of the proposed method includes object detection and analysis applied to the field of security and defence.

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