图 书 馆
基于回归的姿态估计与自动闭塞检测和纠正Regression Based Pose Estimation with Automatic Occlusion Detection and Rectification |
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| 课程网址: | http://videolectures.net/icme2012_radwan_pose_estimation/ |
| 主讲教师: | Ibrahim Ismail Radwan |
| 开课单位: | 堪培拉大学 |
| 开课时间: | 2012-09-18 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Human pose estimation is a classic problem in computer vision. Statistical models based on part-based modelling and the pictorial structure framework have been widely used recently for articulated human pose estimation. However, the performance of these models has been limited due to the presence of self-occlusion. This paper presents a learning-based framework to automatically detect and recover self-occluded body parts. We learn two different models: one for detecting occluded parts in the upper body and another one for the lower body. To solve the key problem of knowing which parts are occluded, we construct Gaussian Process Regression (GPR) models to learn the parameters of the occluded body parts from their corresponding ground truth parameters. Using these models, the pictorial structure of the occluded parts in unseen images is automatically rectified. The proposed framework outperforms a state-of-the-art pictorial structure approach for human pose estimation on 3 different datasets. |
| 关 键 词: | 多媒体; 计算机科学; 计算机视觉 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-15：heyf |
| 阅读次数: | 18 |