Yasufumi Takama

Accuracy-based sampling and reconstruction with adaptive grid for parallel hierarchical tetrahedrization

Recent advances in volume scanning techniques have made the task of acquiring volume data of 3-D objects easier and more accurate. Since the quantity of such acquired data is generally very large, a volume model capable of compressing data while maintaining a specified accuracy is required. The objective of this work is to construct a multi resolution tetrahedra representation of input volume data. This representation adapts to local field properties while preserving their discontinuities. In this paper, we present an accuracy-based adaptive sampling and reconstruction technique, we call an adaptive grid, for hierarchical tetrahedrization of C1 continuous volume data. We have developed a parallel algorithm of adaptive grid generation that recursively bisects tetrahedra gird elements by increasing the number of grid nodes, according to local field properties and such as orientation and curvature of isosurfaces, until the entire volume has been approximated within a specified level of view-invariant accuracy. We have also developed a parallel algorithm that detects and preserves both C0 and C1 discontinuities of field values, without the formation of cracks which normally occur during independent subdivision. Experimental results demonstrate the validity and effusiveness of the proposed approach.

Parallel volume segmentation with tetrahedral adaptive grid

We propose a general-purposed parallel algorithm for volume segmentation, which does not require any prior knowledge on volume nor region. The algorithm provides binary tree structured split-and-merge mechanism to search and localize boundaries along discontinuities and adapts the partition of volume to those detected discontinuities. This algorithm is independent from order of processing or seed selection. And, even though overlapping only one voxel wide boundary between process blocks, by adopting the smoothness-based local feature as homogeneity criteria, consistencies are maintained without overhead of communication between adjacent process blocks. Our efficient hierarchical step-wised mechanism in merging target evaluation makes merge process so simple and efficient that only two brother blocks are considered at each merge step in binary fashion. Experimental results on an artificial and a CT scan volume data are shown.

Tetrahedral adaptive grid for parallel hierarchical tetrahedrization

Recent advances in volume scanning techniques have made the task of acquiring volume data of 3-D objects easier and more accurate. Since the quantity of such acquired data is generally very large, a volume model capable of compressing data while maintaining a specified accuracy is required. The objective of this work is to construct a multi-resolution tetrahedral representation of input volume data. This representation adapts to local field properties while preserving their discontinuities. In this paper, we present an accuracy-based adaptive sampling technique to construct a multi-resolution model, we call a tetrahedral adaptive grid, for hierarchical tetrahedrization of C1 continuous volume data. We have developed a parallel algorithm of tetrahedral adaptive grid generation that recursively bisects tetrahedral gird elements by increasing the number of grid nodes, according to local field properties and such as orientation and curvature of isosurfaces, until the entire volume has been approximated within a specified level of view-invariant accuracy. We have also developed a parallel algorithm that detects and preserves both C0 and C1 discontinuities of field values, without the formation of cracks which normally occur during independent subdivision. Experimental results obtained using a PC cluster system demonstrate the validity and effectiveness of the proposed approach.

Toward Real-time Volume-based Haptic Communication with Realistic Sensation

A volume-based realistic communication system called Haptic Communication is described. The system allows participants to interact in real time with others at remote locations on the network using haptic perception (sense of touch) of soft objects in virtual environments. We constructed the system so that it provides a sense of touch at remote locations in real time. First, an adaptive volume model represents virtual soft objects in PCs at remote locations. Next, the reflection force of the soft object is calculated rapidly and accurately from the parameters of positions and forces at contacting points transmitted via network at each PC. Eventually, the haptic and visual information are rendered by a haptic device (PHANToM) and a volume graphic software in the PCs. We investigated the efficiency of our system via experiments on a simulation of needle insertion with high force feedback rates at two remote locations on a WAN between Ritsumeikan University, Biwako Kusatsu Campus and Shiga Medical University. The experiment results show that the delay due to network traffic is negligible.