  Object tracking is a key aspect in many applications such as augmented
reality in medicine (e.g. tracking a surgical instrument) or robotics. Squared
planar markers have become popular tools for tracking since their pose can be
estimated from their four corners. While using a single marker and a single
camera limits the working area considerably, using multiple markers attached to
an object requires estimating their relative position, which is not trivial,
for high accuracy tracking. Likewise, using multiple cameras requires
estimating their extrinsic parameters, also a tedious process that must be
repeated whenever a camera is moved.
  This work proposes a novel method to simultaneously solve the above-mentioned
problems. From a video sequence showing a rigid set of planar markers recorded
from multiple cameras, the proposed method is able to automatically obtain the
three-dimensional configuration of the markers, the extrinsic parameters of the
cameras, and the relative pose between the markers and the cameras at each
frame. Our experiments show that our approach can obtain highly accurate
results for estimating these parameters using low resolution cameras.
  Once the parameters are obtained, tracking of the object can be done in real
time with a low computational cost. The proposed method is a step forward in
the development of cost-effective solutions for object tracking.
