A physics-based approach to motion capture data processing for virtual plant modeling and simulation

Abstract

Dynamic virtual plant simulation is an attractive research issue in both botany and computer graphics. Data-driven method is an efficient way for motion analysis and animation synthesis. As a widely used tool, motion capture has been used in plant motion data acquisition and analysis. The most prominent and important problem in motion capture for plants is primary data processing such as missing markers reconstruction. This paper presents a novel physics-based approach to motion capture data processing of plants. Firstly, a physics-based mechanics model is found by Lagrangian mechanics for a motion captured plant organ such as a leaf, and then its dynamic mechanical properties are analyzed and relevant model parameters are evaluated. Further, by using the physical model with evaluated parameters, we can calculate the next positions of a maker to reconstruct the missing makers in motion capture sequence. We take an example of a maize leaf and pachira leaf to examine the proposed approach, and the results show that the physics-based method is feasible and effective for plant motion data processing.