图 书 馆
姿态机：通过推理机进行关节姿态估计Pose Machines: Articulated Pose Estimation via Inference Machines |
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| 课程网址: | http://videolectures.net/eccv2014_ramakrishna_pose_machines/ |
| 主讲教师: | Varun Ramakrishna |
| 开课单位: | 卡内基梅隆大学 |
| 开课时间: | 2014-10-29 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | State-of-the-art approaches for articulated human pose estimation are rooted in parts-based graphical models. These models are often restricted to tree-structured representations and simple parametric potentials in order to enable tractable inference. However, these simple dependencies fail to capture all the interactions between body parts. While models with more complex interactions can be defined, learning the parameters of these models remains challenging with intractable or approximate inference. In this paper, instead of performing inference on a learned graphical model, we build upon the inference machine framework and present a method for articulated human pose estimation. Our approach incorporates rich spatial interactions among multiple parts and information across parts of different scales. Additionally, the modular framework of our approach enables both ease of implementation without specialized optimization solvers, and efficient inference. We analyze our approach on two challenging datasets with large pose variation and outperform the state-of-the-art on these benchmarks. |
| 关 键 词: | 图形模型; 数据集 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2020-11-15：zyk |
| 最后编审: | 2020-11-15：zyk |
| 阅读次数: | 45 |