• Journal of KIISE:Computing Practices and Letters
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• v.16 no.2
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• pp.186-200
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• 2010

In order to render global illumination realistically, we need to accurately compute the direct and indirect illumination that represents the light information incoming through complex light paths. In this process, the indirect illumination at given point is greatly affected by surrounding geometries. Harmonic mean distance is a mathematical tool which is often used as a metric indicating the distance from a surface point to its visible objects in 3D space, and plays a key role in such advanced global illumination algorithms as irradiance/radiance caching and ambient occlusion. In this paper, we analyze the accuracy of harmonic mean distance estimated against various environments in the final gathering and photon mapping methods. Based on the experimental results, we discuss our experiences and future directions that may help develop an effective harmonic mean distance computation method in the future.

• The KIPS Transactions:PartA
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• v.11A no.7 s.91
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• pp.555-562
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• 2004

Both global volume reduction and local shape changes of hippocampus within the brain indicate their abnormal neurological states. Hippocampal shape analysis consists of two main steps. First, construct a hippocampal shape representation model ; second, compute a shape similarity from this representation. This paper proposes a novel method for the analysis of hippocampal shape using integrated Octree-based representation, containing meshes, voxels, and skeletons. First of all, we create multi-level meshes by applying the Marching Cube algorithm to the hippocampal region segmented from MR images. This model is converted to intermediate binary voxel representation. And we extract the 3D skeleton from these voxels using the slice-based skeletonization method. Then, in order to acquire multiresolutional shape representation, we store hierarchically the meshes, voxels, skeletons comprised in nodes of the Octree, and we extract the sample meshes using the ray-tracing based mesh sampling technique. Finally, as a similarity measure between the shapes, we compute $L_2$ Norm and Hausdorff distance for each sam-pled mesh pair by shooting the rays fired from the extracted skeleton. As we use a mouse picking interface for analyzing a local shape inter-actively, we provide an interaction and multiresolution based analysis for the local shape changes. In this paper, our experiment shows that our approach is robust to the rotation and the scale, especially effective to discriminate the changes between local shapes of hippocampus and more-over to increase the speed of analysis without degrading accuracy by using a hierarchical level-of-detail approach.