图 书 馆
3D可变形模型的构造用于识别耳朵以及面部的鲁棒性3D Morphable Model Construction for Robust Ear and Face Recognition |
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| 课程网址: | http://videolectures.net/cvpr2010_bustard_3dmm/ |
| 主讲教师: | John David Bustard |
| 开课单位: | 南安普顿大学 |
| 开课时间: | 2010-07-19 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Recent work suggests that the human ear varies significantly between different subjects and can be used for identification. In principle, therefore, using ears in addition to the face within a recognition system could improve accuracy and robustness, particularly for non-frontal views. The paper describes work that investigates this hypothesis using an approach based on the construction of a 3D morphable model of the head and ear. One issue with creating a model that includes the ear is that existing training datasets contain noise and partial occlusion. Rather than exclude these regions manually, a classifier has been developed which automates this process. When combined with a robust registration algorithm the resulting system enables full head morphable models to be constructed efficiently using less constrained datasets. The algorithm has been evaluated using registration consistency, model coverage and minimalism metrics, which together demonstrate the accuracy of the approach. To make it easier to build on this work, the source code has been made available online. |
| 关 键 词: | 识别系统; 的3D可变形模型; 配准算法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-03-12：lxf |
| 阅读次数: | 72 |