Active shape model based on sparse representation
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
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Physics-based particle systems are an effective tool for shape modeling. Also, there has been much interest in the study of shape modeling using deformable contour approaches. In this paper, we describe a new deformable model with electric flows based upon computer simulations of a number of charged particles embedded in an electrostatic system. Making use of optimized numerical techniques, the electric potential associated with the electric field in the simulated system is rapidly calculated using the finite-size particle (FSP) method. The simulation of deformation evolves based upon the vector sum of two interacting forces: one from the electric fields and the other from the image gradients. Inspired by the concept of the signed distance function associated with the entropy condition in the level set framework, we efficiently handle topological changes at the interface. In addition to automatic splitting and merging, the evolving contours enable simultaneous detection of various objects with varying intensity gradients at both interior and exterior boundaries. This electric flows approach for shape modeling allows one to connect electric properties in electrostatic equilibrium and classical active contours based upon the theory of curve evolution. Our active contours can be applied to model arbitrarily complicated objects including shapes with sharp corners and cusps, and to situations where no a priori knowledge about the object's topology and geometry is made. We demonstrate the capabilities of this new algorithm in recovering a wide variety of structures on simulated and real images in both 2D and 3D.