Real-time target classification and tracking by using outdoor PTZ cameras at the edge

Enes Kavakli; Cevahir Çığla; Fikret Alim

doi:10.1117/12.2638833

28 October 2022 Real-time target classification and tracking by using outdoor PTZ cameras at the edge

Enes Kavakli, Cevahir Çığla, Fikret Alim

Proceedings Volume 12275, Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies VI; 122750G (2022) https://doi.org/10.1117/12.2638833
Event: SPIE Security + Defence, 2022, Berlin, Germany

Abstract

Tracking with a Pan-Tilt-Zoom (PTZ) camera has been a research topic in computer vision for many years. Compared to tracking with a still fixed camera, the images captured with a PTZ camera are highly dynamic because the vision becomes difficult under some realistic conditions such as fast camera movements, occlusion and similar objects to the tracked target. Also, compensating for these problems is even more complex on edge system. With the increasing availability of small single-board computers with high parallel processing power capabilities, tracking objects using an onboard computer in real time has become feasible. Although these onboard computers allow a wide variety of computer vision methods to be executed, there is still a need to optimize these methods for running time and power consumption. This paper proposes a hybrid application with low CPU consumption for surveillance objects to detect and track at the edge. To detect the target at the beginning and in the case where the track has been lost, we use the deep learning based YOLOv3 model. This model provides one of the best trade-offs between speed and accuracy in the literature. A kernelized correlation filter is used to track the detected object in real-time. Combining these two algorithms provides high accuracy and speed even on onboard computers. Under a real-time streaming condition, the proposed method yields better results than the original KCF in tracking accuracy and outperforms a deep learning-based tracker when a target has a vast movement.

Conference Presentation

Citation Download Citation

Enes Kavakli, Cevahir Çığla, and Fikret Alim "Real-time target classification and tracking by using outdoor PTZ cameras at the edge", Proc. SPIE 12275, Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies VI, 122750G (28 October 2022); https://doi.org/10.1117/12.2638833

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