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
In this research, we have concentrated on trajectory extraction based on image segmentation and data association in order to provide an economic and complete solution for rapid microfluidic cell migration experiments....In this research, we have concentrated on trajectory extraction based on image segmentation and data association in order to provide an economic and complete solution for rapid microfluidic cell migration experiments. We applied region scalable active contour model to segment the individual cells and then employed the ellipse fitting technique to process touching cells. Subsequently, we have also introduced a topology based technique to associate the cells between consecutive frames. This scheme achieves satisfactory segmentation and tracking results on the datasets acquired by our microfluidic platform.展开更多
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.
文摘In this research, we have concentrated on trajectory extraction based on image segmentation and data association in order to provide an economic and complete solution for rapid microfluidic cell migration experiments. We applied region scalable active contour model to segment the individual cells and then employed the ellipse fitting technique to process touching cells. Subsequently, we have also introduced a topology based technique to associate the cells between consecutive frames. This scheme achieves satisfactory segmentation and tracking results on the datasets acquired by our microfluidic platform.
