粒子群优化人体星形骨架特征矢量量化

Human Star Skeleton Feature Vector Quantization Using PSO

实现了人体星形骨架特征提取,并利用粒子群优化骨架特征矢量的量化。星形骨架通过连接人体质心点到人体四肢及头部端点实现,是一种快速骨架提取技术。把质心点和端点连接,人体星型骨架可以用一个五维矢量Si表示,Si∈Rn,Rn是星型骨架特征空间。时序图像中的人体动作可以用星型骨架序列表示的特征矢量序列S代替。最后用粒子群优化S的特征量化过程,生成特征码本G。

The paper introduces how to extract the human star skeleton and by using the particle swarm to optimize the skeleton characteristic vector quantization.Star skeleton,generated by connecting human center-of-mass point to the human limbs and head endpoint,is a kind of fast skeleton extraction techniques.Connecting center-of-mass point with endpoint,human skeleton could be represented by five dimensional vector Si,Si∈Rn,Rn is the star skeleton feature space.Star skeleton sequence can take the place of the timing sequences of human actions.Finally,we generated the codebook G by using particle swarm optimization quantification process.