Marker localization with a multi-camera system

Abstract

This paper presents a marker localization system consisting of multiple cameras. It is the basis of a real-time robotic motion tracking system aiming for high localization accuracy and high time resolution. These goals are achieved using several cameras with very redundant field-of-views. The paper presents the theoretical background of 3D camera calibration and localization, the localization accuracy measurement setup, and its results. The measurements are obtained using a color marker and an industrial robotic arm for measurement ground truth generation. The Smart Mobile Eyes for Localization (SMEyeL) project is open-source: the source code, all measurement input data and documentation are public available.

Optimizing camera placement for localization accuracy

“…Thus our first goal is to determine the localization accuracy. The calculated localization accuracy can be used to validate the measured localization accuracy in [7].…”

Camera Placement Optimization in Object Localization Systems

“…There is an object in the observed area and its location has to be determined, this process is called localization. Localization can be performed with various methods, an example with measurements is shown in [16], while another method is introduced in [9]. The main idea is that every camera detects the object in its own image and these detections determine half-lines in the world coordinate system.…”

“…The constraints (28) and (29) are substituted into the expanded objective function defined in (16) in case of n = 2. The roots of the partial derivatives with respect to the α i angles are calculated.…”

“…In [16] a localization accuracy measurement is described which corresponds to the theory in [17]. In this present paper the placement of multiple cameras are examined using several objective functions and analytical solutions are given.…”