Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  propose the first algorithm for non-rigid 2D-to-3D shape matching, where the input is a 2D query shape as ll as a 3D target shape and the output is a continuous matching curve represented as a closed contour on the 3D shape.  cast the problem as finding the shortest circular path on the product 3-manifold of the two shapes.  prove that the optimal matching can be computed in polynomial time with a (worst-case) complexity of O(mn2 log(n)), wherem and n denote the number of vertices on the 2D and the 3D shape respectively. Quantitative evaluation confirms that the method provides excellent results for sketch-based deformable 3D shape retrieval.
['Zorah Lahner', 'Emanuele Rodolà', 'Frank R. Schmidt', 'Michael M. Bronstein', 'Daniel Cremers']
I am writing a research paper on a idea Efficient Globally Optimal 2D-to-3D Deformable Shape Matching
[{"from": "human", "value": "I am writing a research paper on a idea Efficient Globally Optimal 2D-to-3D Deformable Shape Matching"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  propose the first algorithm for non-rigid 2D-to-3D shape matching, where the input is a 2D query shape as ll as a 3D target shape and the output is a continuous matching curve represented as a closed contour on the 3D shape.  cast the problem as finding the shortest circular path on the product 3-manifold of the two shapes.  prove that the optimal matching can be computed in polynomial time with a (worst-case) complexity of O(mn2 log(n)), wherem and n denote the number of vertices on the 2D and the 3D shape respectively. Quantitative evaluation confirms that the method provides excellent results for sketch-based deformable 3D shape retrieval."}]