An efficient voxelization algorithm is presented for polygonal models by using the hardware support for the 2 D rasterization algorithm and the GPU programmable function to satisfy the volumetric display system. The v...An efficient voxelization algorithm is presented for polygonal models by using the hardware support for the 2 D rasterization algorithm and the GPU programmable function to satisfy the volumetric display system. The volume is sampled into slices by the rendering hardware and then slices are rasterated into a series of voxels. A composed buffer is used to record encoded voxels of the target volume to reduce the graphic memory requirement. In the algorithm, dynamic vertexes and index buffers are used to improve the voxelization efficiency. Experimental results show that the algorithm is efficient for a true 3-D display system.展开更多
A new motion retargeting algorithm is presented, which adapts me motion capture data to a new character. To make the resulting motion realistic, the physically-based optimization method is adopted. However, the optimi...A new motion retargeting algorithm is presented, which adapts me motion capture data to a new character. To make the resulting motion realistic, the physically-based optimization method is adopted. However, the optimization process is difficult to converge to the optimal value because of high complexity of the physical human model. In order to address this problem, an appropriate simplified model automatically determined by a motion analysis technique is utilized, and then motion retargeting with this simplified model as an intermediate agent is implemented. The entire motion retargeting algorithm involves three steps of nonlinearly constrained optimization： forward retargeting, motion scaling and inverse retargeting. Experimental results show the validity of this algorithm.展开更多
Probabilistic models are commonly used in computational medicine for diagnostics. Smoking cessation is an important issue of modern medicine. According to statistics about third part of male in global population are s...Probabilistic models are commonly used in computational medicine for diagnostics. Smoking cessation is an important issue of modern medicine. According to statistics about third part of male in global population are smokers. It is important to develop new approaches for smoking cessation treatment including methods of early diagnosis and development of individual treatment programs for each patient according to his or her physical peculiarities. One of the promising methods is computerized approach for tobacco treatment including electronic survey and computer data analysis. In this work we propose a probabilistic model based on Markov chain for estimation of patient behavior in the process on medical survey. This analysis can help to find out patient＇s individual characteristics and develop effective personal treatment program. Based on probabilistic model software was developed with aim to enhance diagnosis and developing individual smoking cessation treatment programs for each patient.展开更多
文摘An efficient voxelization algorithm is presented for polygonal models by using the hardware support for the 2 D rasterization algorithm and the GPU programmable function to satisfy the volumetric display system. The volume is sampled into slices by the rendering hardware and then slices are rasterated into a series of voxels. A composed buffer is used to record encoded voxels of the target volume to reduce the graphic memory requirement. In the algorithm, dynamic vertexes and index buffers are used to improve the voxelization efficiency. Experimental results show that the algorithm is efficient for a true 3-D display system.
文摘A new motion retargeting algorithm is presented, which adapts me motion capture data to a new character. To make the resulting motion realistic, the physically-based optimization method is adopted. However, the optimization process is difficult to converge to the optimal value because of high complexity of the physical human model. In order to address this problem, an appropriate simplified model automatically determined by a motion analysis technique is utilized, and then motion retargeting with this simplified model as an intermediate agent is implemented. The entire motion retargeting algorithm involves three steps of nonlinearly constrained optimization： forward retargeting, motion scaling and inverse retargeting. Experimental results show the validity of this algorithm.
文摘Probabilistic models are commonly used in computational medicine for diagnostics. Smoking cessation is an important issue of modern medicine. According to statistics about third part of male in global population are smokers. It is important to develop new approaches for smoking cessation treatment including methods of early diagnosis and development of individual treatment programs for each patient according to his or her physical peculiarities. One of the promising methods is computerized approach for tobacco treatment including electronic survey and computer data analysis. In this work we propose a probabilistic model based on Markov chain for estimation of patient behavior in the process on medical survey. This analysis can help to find out patient＇s individual characteristics and develop effective personal treatment program. Based on probabilistic model software was developed with aim to enhance diagnosis and developing individual smoking cessation treatment programs for each patient.
