Knowledge Commons of Institute of Automation,CAS
Bilateral Ordinal Relevance Multi-instance Regression for Facial Action Unit Intensity Estimation | |
Yong Zhang1,2; Rui Zhao3; Weiming Dong1; Bao-Gang Hu1; Qiang Ji3 | |
2018-06 | |
会议名称 | 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) |
会议录名称 | IEEE/CVF Conference on Computer Vision and Pattern Recognition |
会议日期 | 2018-6 |
会议地点 | Salt Lake City, Utah |
出版者 | IEEE |
摘要 | Automatic intensity estimation of facial action units (AUs) is challenging in two aspects. First, capturing subtle changes of facial appearance is quite difficult. Second, the annotation of AU intensity is scarce and expensive. Intensity annotation requires strong domain knowledge thus only experts are qualified. The majority of methods directly apply supervised learning techniques to AU intensity estimation while few methods exploit unlabeled samples to improve the performance. In this paper, we propose a novel weakly supervised regression model-Bilateral Ordinal Relevance Multi-instance Regression (BORMIR), which learns a frame-level intensity estimator with weakly labeled sequences. From a new perspective, we introduce relevance to model sequential data and consider two bag labels for each bag. The AU intensity estimation is formulated as a joint regressor and relevance learning problem. Temporal dynamics of both relevance and AU intensity are leveraged to build connections among labeled and unlabeled image frames to provide weak supervision. We also develop an efficient algorithm for optimization based on the alternating minimization framework. Evaluations on three expression databases demonstrate the effectiveness of the proposed method. |
收录类别 | EI |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/23902 |
专题 | 多模态人工智能系统全国重点实验室_三维可视计算 |
通讯作者 | Qiang Ji |
作者单位 | 1.NLPR, Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences 3.Rensselaer Polytechnic Institute |
第一作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Yong Zhang,Rui Zhao,Weiming Dong,et al. Bilateral Ordinal Relevance Multi-instance Regression for Facial Action Unit Intensity Estimation[C]:IEEE,2018. |
条目包含的文件 | 条目无相关文件。 |
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