使用更丰富的模型进行足球运动员的关节姿势估计Using Richer Models for Articulated Pose Estimation of Footballers |
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课程网址: | http://videolectures.net/bmvc2012_kazemi_pose_estimation/ |
主讲教师: | Vahid Kazemi |
开课单位: | 皇家理工学院 |
开课时间: | 信息不详。欢迎您在右侧留言补充。 |
课程语种: | 英语 |
中文简介: | 我们提出了一个全自动的程序,以重建一个人的姿态三维图像从多个视图。我们演示了一种使用SVM-Rank学习更复杂模型的新方法,以重新排列一组高得分配置。新模型在很多情况下可以解决基于图形结构模型中经常出现的肢体重复计数问题。我们解决了翻转歧义的问题,以便在所有视图中找到二维预测的正确对应关系。我们对数据集上的二维预测方法进行了改进。我们证明,在许多情况下,结果是足够好的,以全自动三维重建与未校准的相机。 |
课程简介: | We present a fully automatic procedure for reconstructing the pose of a person in 3D from images taken from multiple views. We demonstrate a novel approach for learning more complex models using SVM-Rank, to reorder a set of high scoring configurations. The new model in many cases can resolve the problem of double counting of limbs which happens often in the pictorial structure based models. We address the problem of flipping ambiguity to find the correct correspondences of 2D predictions across all views. We obtain improvements for 2D prediction over the state of art methods on our dataset. We show that the results in many cases are good enough for a fully automatic 3D reconstruction with uncalibrated cameras. |
关 键 词: | 全自动程序; 图像重建3D人物; SVM-Rank |
课程来源: | 视频讲座网 |
最后编审: | 2019-10-22:cwx |
阅读次数: | 37 |