首页> 外文会议>映像情報メディア学会2017年冬季大会講演予稿集 >Front View Generation of 2D Skeleton Poses Using Homography Transformation in an Adaptive Window
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Front View Generation of 2D Skeleton Poses Using Homography Transformation in an Adaptive Window

机译:在自适应窗口中使用同构变换实现2D骨骼姿势的前视图生成

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With the development of human pose estimation technology from an image/video, 2D skeleton pose becomesrnubiquitously available. Different from the traditional 3D poses, it is more challenging to understand 2D poses such as actionrnrecognition because joint positions in 2D poses change a lot when the camera changes its capturing angle. Thus, it is essentialrnto generate a front view pose from a non-front view one to avoid the camera angle problem. In this paper, we propose a novelrnalgorithm for front view generation of 2D poses using homography transformation in an adaptive window. Our experimentsrnshow that the algorithm can greatly reduce the errors when computing the parameters of homography transformation.
机译:随着来自图像/视频的人体姿势估计技术的发展,二维骨架姿势变得无处不在。与传统的3D姿势不同,理解2D姿势(例如动作识别)更具挑战性,因为当相机更改其捕获角度时,2D姿势中的关节位置会发生很大变化。因此,必须从非正视图产生正视图姿势以避免相机角度问题。在本文中,我们提出了一种在自适应窗口中使用单应变换来生成2D姿势的前视图的新颖算法。我们的实验表明,该算法在计算单应变换参数时可以大大减少误差。

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