International audienceThis paper presents a planar curve matching framework based on computing similarities between shape parts. We propose an elastic similarity measure issued from shape geodesics in the shape space. As the transition from global matching to partial matching leads to additional difficulties, we bypass them with a shape decomposition process based on the discrete curve evolution (DCE). This decomposition aims to obtain significant parts to match and it leads to a robust and efficient 2D shape matching algorithm. The comparison of the proposed method with the state of the art demonstrates its ability to handle elastic deformations leading to an overall optimal partial correspondence between shapes
We propose a novel method for computing a geometri-cally consistent and spatially dense matching bet...
Abstract. We propose a novel method for computing a geometrically consistent and spatially dense mat...
In elastic shape analysis, a representation of a shape is invariant to translation, scaling, rotatio...
International audienceThis paper presents a planar curve matching framework based on computing simil...
International audienceThis paper presents a planar curve matching framework based on computing simil...
International audienceThis paper presents a planar curve matching framework based on computing simil...
We propose an efficient representation for studying shapes of closed curves in Rn. This paper combin...
In this paper, we study a class of Riemannian metrics on the space of unparametrized curves and deve...
We propose a novel method for computing a geometri-cally consistent and spatially dense matching bet...
Shape matching is a fundamental operation in digital geometry processing and computer graphics. Chal...
AbstractThis note addresses the following shape matching problem: given a ‘template’ shape, numerica...
In this paper, we study a class of Riemannian metrics on the space of unparametrized curves and deve...
We define distances between geometric curves by the square root of the minimal energy required to tr...
This paper illustrates and extends an efficient framework, called the square-root-elastic (SRE) fram...
AbstractDetermining the similarity of two shapes is a significant task in both machine and human vis...
We propose a novel method for computing a geometri-cally consistent and spatially dense matching bet...
Abstract. We propose a novel method for computing a geometrically consistent and spatially dense mat...
In elastic shape analysis, a representation of a shape is invariant to translation, scaling, rotatio...
International audienceThis paper presents a planar curve matching framework based on computing simil...
International audienceThis paper presents a planar curve matching framework based on computing simil...
International audienceThis paper presents a planar curve matching framework based on computing simil...
We propose an efficient representation for studying shapes of closed curves in Rn. This paper combin...
In this paper, we study a class of Riemannian metrics on the space of unparametrized curves and deve...
We propose a novel method for computing a geometri-cally consistent and spatially dense matching bet...
Shape matching is a fundamental operation in digital geometry processing and computer graphics. Chal...
AbstractThis note addresses the following shape matching problem: given a ‘template’ shape, numerica...
In this paper, we study a class of Riemannian metrics on the space of unparametrized curves and deve...
We define distances between geometric curves by the square root of the minimal energy required to tr...
This paper illustrates and extends an efficient framework, called the square-root-elastic (SRE) fram...
AbstractDetermining the similarity of two shapes is a significant task in both machine and human vis...
We propose a novel method for computing a geometri-cally consistent and spatially dense matching bet...
Abstract. We propose a novel method for computing a geometrically consistent and spatially dense mat...
In elastic shape analysis, a representation of a shape is invariant to translation, scaling, rotatio...