An evolutionary algorithm for physical motion analysis

This paper presents an approach to motion understanding, through identification of physical pa- rameters from image sequences. It is based on a family of particle-base d physical models where deformable objects are represented as sets of weighted particles and their interactions. The inter- action model presented derives from an energy potential, using dual bonds (extension springs) and ternary bonds (torsional springs). An original dynamical motion analysis algorithm is described, which extracts physical animation parameters (springs lengths, angles, stiffness...) through the processing of an image sequence. Ge- netic techniques are employed to perform the fitting of parameters in an analysis-by-synthesis scheme. Experimental test results on synthetic sequences are reported.