Multi-view Active Appearance Models for the X-Ray Based Analysis of Avian Bipedal Locomotion

Abstract. Many fields of research in biology, motion science and robotics depend on the understanding of animal locomotion. Therefore, numerous experiments are performed using high-speed biplanar x-ray acquisition systems which record sequences of walking animals. Until now, the evalu-ation of these sequences is a very time-consuming task, as human experts have to manually annotate anatomical landmarks in the images. There-fore, an automation of this task at a minimum level of user interaction is worthwhile. However, many difficulties in the data—such as x-ray occlu-sions or anatomical ambiguities—drastically complicate this problem and require the use of global models. Active Appearance Models (AAMs) are known to be capable of dealing with occlusions, but have problems with ambiguities. We therefore analyze the application of multi-view AAMs in the scenario stated above and show that they can effectively han-dle uncertainties which can not be dealt with using single-view models. Furthermore, preliminary studies on the tracking performance of huma