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Application of 2D Homography for High Resolution Traffic Data Collection using CCTV Cameras by Zhang, Linlin; Yu, Xiang; Daud, Abdulateef; Mussah, Abdul Rashid; Adu-Gyamfi, Yaw is a scholarly article available to read on EtoBox.

What is Application of 2D Homography for High Resolution Traffic Data Collection using CCTV Cameras about?

Traffic cameras remain the primary source data for surveillance activities such as congestion and incident monitoring. To date, State agencies continue to rely on manual effort to extract data from networked cameras due to limitations of the current automatic vision systems including requirements for complex camera calibration and inability to generate high resolution data. This study implements a three-stage video analytics framework for extracting high-resolution traffic data such vehicle counts, speed, and acceleration from infrastructure-mounted CCTV cameras. The key components of the framework include object recognition, perspective transformation, and vehicle trajectory reconstruction for traffic data collection. First, a state-of-the-art vehicle recognition model is implemented to detect and classify vehicles. Next, to correct for camera distortion and reduce partial occlusion, an algorithm inspired by two-point linear perspective is utilized to extracts the region of interest (ROI) automatically, while a 2D homography technique transforms the CCTV view to bird's-eye view (BEV). Cameras are calibrated with a two-layer matrix system to enable the extraction of speed and accel

Author

Zhang, Linlin; Yu, Xiang; Daud, Abdulateef; Mussah, Abdul Rashid; Adu-Gyamfi, Yaw

Published

2024

Language

EN