1) expression intensity
表情强度
1.
A method of measuring the expression intensity based on facial feature point tracking is presented,which is based on the L-K optical flow algorithm and uses the amended feature point tracking to track facial feature points.
提出了一种基于特征点跟踪的面部表情强度度量方法。
2.
The algorithm can also synthesize the expression image in light of given expression intensity values.
根据分解的结果,可以实现表情强度的估计和表情的识别,也可以根据给定的表情强度参数合成各种表情图像,克服了表情强度估计、表情的分解与合成中需要手工标注特征点的问题,降低了训练集的不同对表情识别的影响。
2) intensity variation of facial expression
表情强度变化
3) expression intensity model
表情强度模型
5) emotion intensity
情绪强度
1.
A solution for the estimation of impatience intensity was proposed as follows:a mathematical modeling for impatience was advanced to build a double-mode feature model,expressing impatience with both facial and action\'s expression,and then,emotion intensity was estimated and it was divided into three grades by Double layers of Gaussian Mixture Hidden Markov Model(DMHMM).
针对急躁情绪的强度估计问题,提出了解决方案,其思路是:对急躁情绪进行数学建模,构建双模态特征模型,分别采用面部表情和动作表情(头部运动)双模态信息来表征急躁情绪;然后用双层高斯混合隐马尔科夫模型(DMHMM)对情绪强度进行估计,得到情绪强度的三个等级。
补充资料：表光合强度(见光合强度)
表光合强度(见光合强度)
forecast of sowing or transplanting time
b iaoguanghe qiangdu表光合强度见光合强度
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条