Traditional videometric approach cannot be used to measure the pose deformation of objects in a large viewing field or
of non-intervisible objects in the large structures, however, pose-relay videometric using camera series or camera
network can be used to overcome the difficulties. It is a usual practice to fuse the pose data by using the constrained
conditions abounding in the camera network in order to improve the measurement precision. This article first provides a
brief introduction to the principle underlying the method of camera network videometric and an analysis of its constraint
conditions in light of the graph theory; then it proposes and experiments on an adjustment-based data fusion method in
the pose relay videometric using camera network; finally, it manifests a numerical simulation on the proposed method.
The results show that it is able to effectively suppress noises and improve the measurement precision because they can
take full advantages of the constraint conditions intrinsic to the camera network.
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