Pedestrian Tracking with Monocular Camera: Simple 2D Filter Springing From 3D Modeling

Abstract

A simple and real-time 2D single-object visual tracker is derived based on first-principle modeling in 3D, which was introduced in previous work. An inverse of the nonlinear perspective projection is followed by a simple approximation assuming that the pedestrian moves with a fixed depth in front of the camera. The resulting 2D tracking algorithm appears to have a similar form as the state-of-the-art single-object tracker from BoT-SORT, is easy to implement, and its parameters have convenient meaning. Its performance is assessed statistically using the publicly available MOT17 dataset.