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3D anatomical landmarks play an important role in health research. Theirautomated prediction/localization thus becomes a vital task. In this paper, weintroduce a deformation method for 3D anatomical landmarks prediction. Itutilizes a source model with anatomical landmarks which are annotated byclinicians, and deforms this model non-rigidly to match the target model. Twoconstraints are introduced in the optimization, which are responsible foralignment and smoothness, respectively. Experiments are performed on ourdataset and the results demonstrate the robustness of our method, and show thatit yields better performance than the state-of-the-art techniques in mostcases.

Anatomical Landmarks Localization for 3D Foot Point Clouds