Coordinated Tracking Of Multiple Point Targets With Multiple Cameras

Jeffrey Labuz

doi:10.1117/12.948938

5 January 1989 Coordinated Tracking Of Multiple Point Targets With Multiple Cameras

Jeffrey Labuz

Proceedings Volume 1003, Sensor Fusion: Spatial Reasoning and Scene Interpretation; (1989) https://doi.org/10.1117/12.948938
Event: 1988 Cambridge Symposium on Advances in Intelligent Robotics Systems, 1988, Boston, MA, United States

Abstract

Presented in this paper are the system and measurement models, and the recursive filter equations, for an extended Kalman filter (EKF) to be used in tracking video point targets. The filter is designed to maintain estimates of a target's position, velocity, and acceleration in three dimensions (3D) based on two-dimensional (2D) measurements of the target's bearings as observed by several cameras. The geometric mapping from object points in 3D world coordinates to image points in 2D image coordinates is modeled by the central projection for pinhole cameras. The recursive equations of the EKF incorporate the Jacobian of this nonlinear camera transformation.

Citation Download Citation

Jeffrey Labuz "Coordinated Tracking Of Multiple Point Targets With Multiple Cameras", Proc. SPIE 1003, Sensor Fusion: Spatial Reasoning and Scene Interpretation, (5 January 1989); https://doi.org/10.1117/12.948938

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