摘要
人体朝向判定是人体模型自动配准、人体运动分析和数据驱动动画的基础.针对现有人体朝向判定方法存在的对模型姿态过于敏感、计算结果不准确等问题,提出一种基于支持向量机的姿态无关人体朝向判定方法.首先分析人体朝向与人体下肢骨骼的关系,构造由下肢骨骼与人体朝向的夹角组成的特征向量,然后利用支持向量机理论训练朝向判定分类器,实现不同姿态人体朝向判定.实验结果表明,文中所构造的特征向量具有较好的线性可分性,朝向判定分类器可以有效地识别各种姿态的人体朝向,并可以非常方便地集成到现有的骨骼提取算法中.
Human body orientation recognition is a fundamental preprocessing task in registering two human body surfaces,analyzing motions of human bodies,and generating data-driven animations.The existing methods for human body orientation recognition are usually pose dependent and not very robust.To solve this problem,we propose an automatic pose-independent method for human body orientation recognition,which is based on SVM and geometric features.Specifically,the geometric features are constructed by using the relations between the joints of the lower limbs and body orientation.The SVM classifier is then trained to determine the body orientations.The experimental results show the effectiveness of the features（with good linear separability） and the SVM classifier can achieve very good performance in a pose-independent manner.Moreover,it is convenient to integrate this method into the existing approaches of extracting the skeleton from human body shapes.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2010年第12期2061-2066,共6页
Journal of Computer-Aided Design & Computer Graphics
基金
国家"八六三"高技术研究发展计划(2007AA01Z337)
北京市教育委员会科技计划面上项目(KM200910005020)
