目的:综合评价单次鼻腔喷入催产素对精神疾病患者面部情绪识别的影响。方法:通过对Pubmed和Web of Science进行检索,并对相关的参考文献进行追踪,共纳入5篇随机对照研究,运用Stata12.0软件对纳入的文献进行分析。结果:固定效应模型显示...目的:综合评价单次鼻腔喷入催产素对精神疾病患者面部情绪识别的影响。方法:通过对Pubmed和Web of Science进行检索,并对相关的参考文献进行追踪,共纳入5篇随机对照研究,运用Stata12.0软件对纳入的文献进行分析。结果:固定效应模型显示单次鼻腔喷入催产素对精神疾病患者的面部情绪识别的合并效应量Hedges’g值为0.257(P<0.05),95%CI(0.004,0.509)。结论:单次鼻腔喷入催产素能够提高精神疾病患者的面部情绪识别能力。展开更多
Facial expression recognition consists of determining what kind of emotional content is presented in a human face. The problem presents a complex area for exploration, since it encompasses face acquisition, facial fea...Facial expression recognition consists of determining what kind of emotional content is presented in a human face. The problem presents a complex area for exploration, since it encompasses face acquisition, facial feature tracking, facial ex- pression classification. Facial feature tracking is of the most interest. Active Appearance Model (AAM) enables accurate tracking of facial features in real-time, but lacks occlusions and self-occlusions. In this paper we propose a solution to improve the accuracy of fitting technique. The idea is to include occluded images into AAM training data. We demonstrate the results by running ex- periments using gradient descent algorithm for fitting the AAM. Our experiments show that using fitting algorithm with occluded training data improves the fitting quality of the algorithm.展开更多
文摘目的:综合评价单次鼻腔喷入催产素对精神疾病患者面部情绪识别的影响。方法:通过对Pubmed和Web of Science进行检索,并对相关的参考文献进行追踪,共纳入5篇随机对照研究,运用Stata12.0软件对纳入的文献进行分析。结果:固定效应模型显示单次鼻腔喷入催产素对精神疾病患者的面部情绪识别的合并效应量Hedges’g值为0.257(P<0.05),95%CI(0.004,0.509)。结论:单次鼻腔喷入催产素能够提高精神疾病患者的面部情绪识别能力。
文摘Facial expression recognition consists of determining what kind of emotional content is presented in a human face. The problem presents a complex area for exploration, since it encompasses face acquisition, facial feature tracking, facial ex- pression classification. Facial feature tracking is of the most interest. Active Appearance Model (AAM) enables accurate tracking of facial features in real-time, but lacks occlusions and self-occlusions. In this paper we propose a solution to improve the accuracy of fitting technique. The idea is to include occluded images into AAM training data. We demonstrate the results by running ex- periments using gradient descent algorithm for fitting the AAM. Our experiments show that using fitting algorithm with occluded training data improves the fitting quality of the algorithm.
