报告题目：Quasi Non-Negative Quaternion Matrix Factorization with Application to Color Face Recognition

报 告 人：柯艺芬 副教授

报告地点：腾讯会议386744422

报告时间：2024年4月2日星期二20: 00-21:00

报告摘要：To address the non-negativity dropout problem of quaternion models, a novel quasi non-negative quaternion matrix factorization (QNQMF) model is presented for color image processing. To implement QNQMF, the quaternion projected gradient algorithm and the quaternion alternating direction method of multipliers are proposed via formulating QNQMF as the non-convex constraint quaternion optimization problems. Some properties of the proposed algorithms are studied. The numerical experiments on the color image reconstruction show that these algorithms encoded on the quaternion perform better than these algorithms encoded on the red, green and blue channels. Furthermore, we apply the proposed algorithms to the color face recognition. Numerical results indicate that the accuracy rate of face recognition on the quaternion model is better than on the red, green and blue channels of color image as well as single channel of gray level images for the same data, when large facial expressions and shooting angle variations are presented.

报告人简介：柯艺芬, 福建师范大学beat365官方网站副教授，博士生导师。现任中国数学会计算数学分会第十一届理事会理事、中国高等教育学会教育数学专业委员会第五届理事会理事、分析数学及应用教育部重点实验室骨干成员。入选福建省高层次人才、福建师范大学青年英才计划、中国博士后创新人才支持计划。主持国家重点研发计划项目子课题、国家自然科学基金、福建省自然科学基金项目等，以第一作者发表SCI学术论文40余篇。