Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  propose a dynamical model-based approach for tracking the shape and deformation of highly deforming objects from time-varying imagery. Previous works have assumed that the object deformation is smooth, which is realistic for the tracking problem, but most have restricted the deformation to belong to a finite-dimensional group, such as affine motions, or to finitely-parameterized models. This, hover, limits the accuracy of the tracking scheme.  exploit the smoothness assumption implicit in previous work, but  lift the restriction to finite-dimensional motions/deformations. To do so,  derive analytical tools to define a dynamical model on the (infinite-dimensional) space of curves. To demonstrate the application of these ideas to object tracking,  construct a simple dynamical model on shapes, which is a first-order approximation to any dynamical system.  then derive an associated nonlinear filter that estimates and predicts the shape and deformation of a object from image measurements.
['Ganesh Sundaramoorthi', 'Andrea C. Mennucci', 'Stefano Soatto', 'Anthony J. Yezzi']
I am writing a research paper on a idea Tracking deforming objects by filtering and prediction in the space of curves
[{"from": "human", "value": "I am writing a research paper on a idea Tracking deforming objects by filtering and prediction in the space of curves"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  propose a dynamical model-based approach for tracking the shape and deformation of highly deforming objects from time-varying imagery. Previous works have assumed that the object deformation is smooth, which is realistic for the tracking problem, but most have restricted the deformation to belong to a finite-dimensional group, such as affine motions, or to finitely-parameterized models. This, hover, limits the accuracy of the tracking scheme.  exploit the smoothness assumption implicit in previous work, but  lift the restriction to finite-dimensional motions/deformations. To do so,  derive analytical tools to define a dynamical model on the (infinite-dimensional) space of curves. To demonstrate the application of these ideas to object tracking,  construct a simple dynamical model on shapes, which is a first-order approximation to any dynamical system.  then derive an associated nonlinear filter that estimates and predicts the shape and deformation of a object from image measurements."}]