可随机存取预测的人体姿态数据无损压缩方法

王鹏杰 已出版文章查询
王鹏杰
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1 张明敏 已出版文章查询
张明敏
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2 王江 已出版文章查询
王江
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1 宋海玉 已出版文章查询
宋海玉
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1 潘志庚 已出版文章查询
潘志庚
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1大连民族大学计算机科学与工程学院 大连 116600

2浙江大学CADCG国家重点实验室 杭州 310058

3杭州师范大学虚拟现实与人机交互研究中心 杭州 310036


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当前的人体运动无损压缩方法多是将人体姿态放入一个前后连续的预测空间, 使得当需要某一姿态时必须将其前预测空间的姿态全部处理完成, 增加了解压时间和内存占用. 针对这一问题, 提出一种预测器级可随机存取预测的人体姿态数据无损压缩方法. 该方法将组织良好的人体姿态集作为处理对象, 首先采用两步的聚类方法分层对人体动作及姿态进行归类整理, 整理后将相似的人体姿态聚集到一个数据预测空间; 然后提出一个带参的均值预测器对聚集姿态集中的当前姿态进行预测; 最后采用熵编码算法对预测值和真实值之间差值进行压缩编码, 得到压缩后的精简数据. 实验结果表明, 文中方法在解压缩时间及压缩比方面优于传统的方法; 在人体动画, 虚拟现实等需要实时获取精确运动数据的应用中具有广泛应用前景.

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语种: 中文   

基金国家自然科学基金(61300089, 61332017)

关键词运动捕获 无损压缩 角色动画 预测器 姿态压缩


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