Cross-cascading regression for simultaneous head pose estimation and facial landmark detection | |
Zhang, Wei![]() ![]() ![]() ![]() | |
2018-08 | |
会议名称 | Chinese Conference on Biometric Recognition |
会议日期 | 2018-08 |
会议地点 | China |
摘要 | Head pose estimation and facial landmark localization are crucial problems which have a large amount of applications. We propose a cross-cascading regression network which simultaneously perform head pose estimation and facial landmark detection by integrating information embedded in both head poses and facial landmarks. The network consists of two sub-models, one responsible for head pose estimation and the other for facial landmark localization, and a convolutional layer (channel unification layer) which enables the communication of feature maps generated by both sub-models. To be specific, we adopt integral operation for both pose and landmark coordinate regression, and exploit expectation instead of maximum value to estimate head pose and locate facial landmarks. Results of extensive experiments demonstrate that our approach achieves state-of-the-art performance on the challenging AFLW dataset. |
是否为代表性论文 | 否 |
七大方向——子方向分类 | 生物特征识别 |
国重实验室规划方向分类 | 视觉信息处理 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/55267 |
专题 | 模式识别实验室 |
作者单位 | Institute of Automation, Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Zhang, Wei,Zhang, Hongwen,Li, Qi,et al. Cross-cascading regression for simultaneous head pose estimation and facial landmark detection[C],2018. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
978-3-319-97909-0_16(777KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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