We propose new techniques for 2-D shape/contour completion, which is one of the important research topics related to shape analysis and computer vision, e.g. the detection of incomplete objects due to occlusion and no...We propose new techniques for 2-D shape/contour completion, which is one of the important research topics related to shape analysis and computer vision, e.g. the detection of incomplete objects due to occlusion and noises. The purpose of shape completion is to find the optimal curve segments that fill the missing contour parts, so as to acquire the best estimation of the original complete object shapes. Unlike the previous work using local smoothness or minimum curvature priors, we solve the problem under a Bayesian formulation taking advantage of global shape prior knowledge. With the priors, our methods are expert in recovering significant shape structures and dealing with large occlusion cases. There are two different priors adopted in this paper: (i) A generic prior model that prefers minimal global shape transformation (including non-rigid deformation and affine transformation with respect to a reference object shape) of the recovered complete shape; and (ii) a class-specific shape prior model learned from training examples of an object category, which prefers the reconstructed shape to follow the learned shape variation models of the category. Efficient contour completion algorithms are suggested corresponding to the two types of priors. Our experimental results demonstrate the advantage of the proposed shape completion approaches compared to the existing techniques, especially for objects with complex structure under severe occlusion.展开更多
This paper presents a novel algorithm for planar G1 interpolation using typical curves with monotonic curvature.The G1 interpolation problem is converted into a system of nonlinear equations and sufficient conditions ...This paper presents a novel algorithm for planar G1 interpolation using typical curves with monotonic curvature.The G1 interpolation problem is converted into a system of nonlinear equations and sufficient conditions are provided to check whether there is a solution.The proposed algorithm was applied to a curve completion task.The main advantages of the proposed method are its simple construction,compatibility with NURBS,and monotonic curvature.展开更多
基金supported by the National Basic Research Program of China (2009CB320904)the National Natural Science Foundation of China (61103087,61121002 and 61272027)the Scientific Research Foundation for the Returned Overseas Chinese Scholars,State Education Ministry
文摘We propose new techniques for 2-D shape/contour completion, which is one of the important research topics related to shape analysis and computer vision, e.g. the detection of incomplete objects due to occlusion and noises. The purpose of shape completion is to find the optimal curve segments that fill the missing contour parts, so as to acquire the best estimation of the original complete object shapes. Unlike the previous work using local smoothness or minimum curvature priors, we solve the problem under a Bayesian formulation taking advantage of global shape prior knowledge. With the priors, our methods are expert in recovering significant shape structures and dealing with large occlusion cases. There are two different priors adopted in this paper: (i) A generic prior model that prefers minimal global shape transformation (including non-rigid deformation and affine transformation with respect to a reference object shape) of the recovered complete shape; and (ii) a class-specific shape prior model learned from training examples of an object category, which prefers the reconstructed shape to follow the learned shape variation models of the category. Efficient contour completion algorithms are suggested corresponding to the two types of priors. Our experimental results demonstrate the advantage of the proposed shape completion approaches compared to the existing techniques, especially for objects with complex structure under severe occlusion.
基金This work was supported by opening fund of State Key Laboratory of Lunar and Planetary Sciences(Macao University of Science and Technology),No.119/2017/A3the Natural Science Foundation of China,Nos.61572056 and 61872347+1 种基金the Special Plan for the Development of Distinguished Young Scientists of ISCAS,No.Y8RC535018the Science and Technology Development Fund of Macao,No.0105/2020/A3.
文摘This paper presents a novel algorithm for planar G1 interpolation using typical curves with monotonic curvature.The G1 interpolation problem is converted into a system of nonlinear equations and sufficient conditions are provided to check whether there is a solution.The proposed algorithm was applied to a curve completion task.The main advantages of the proposed method are its simple construction,compatibility with NURBS,and monotonic curvature.
