sajid hussain - Academia.edu (original) (raw)
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Manonmaniam Sundaranar University, Tamilnadu, India
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Papers by sajid hussain
In computer graphics image synthesis algorithms like ray tracing, the mesh complexity decreases t... more In computer graphics image synthesis algorithms like ray tracing, the mesh complexity decreases the performance of these algorithms. Therefore, the need arises to reduce the complexity of these meshes and at the same time preserving the salient features of the shape. Initial selection of vertices for mesh simplification heavily relates with the quality of the simplified meshes. In this paper, we present a greedy approach to select initial vertex contraction pairs to preserve salient features in the simplified meshes. The greedy algorithm exploits the property of meshes where vertices forming small features contain less number of edges. The technique selects vertices connected with large number of edges and makes them potential candidates for contraction according to a given cost function. The purpose is to first simplify those regions which are enriched with number of triangles and preserve small details of the shape constructed with small number of triangles. Our technique preserves very small details in the shape even after considerable simplification as compared to other existing techniques. Initial experiments show promising results with preserved salient features.
In computer graphics image synthesis algorithms like ray tracing, the mesh complexity decreases t... more In computer graphics image synthesis algorithms like ray tracing, the mesh complexity decreases the performance of these algorithms. Therefore, the need arises to reduce the complexity of these meshes and at the same time preserving the salient features of the shape. Initial selection of vertices for mesh simplification heavily relates with the quality of the simplified meshes. In this paper, we present a greedy approach to select initial vertex contraction pairs to preserve salient features in the simplified meshes. The greedy algorithm exploits the property of meshes where vertices forming small features contain less number of edges. The technique selects vertices connected with large number of edges and makes them potential candidates for contraction according to a given cost function. The purpose is to first simplify those regions which are enriched with number of triangles and preserve small details of the shape constructed with small number of triangles. Our technique preserves very small details in the shape even after considerable simplification as compared to other existing techniques. Initial experiments show promising results with preserved salient features.