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Estimating 2D Multi-hand Poses from Single Depth Images

机译:从单深度图像估计二维多手姿势

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We present a novel framework based on Pictorial Structure (PS) models to estimate 2D multi-hand poses from depth images. Most existing single-hand pose estimation algorithms are either subject to strong assumptions or depend on a weak detector to detect the human hand. We utilize Mask R-CNN to avoid both aforementioned constraints. The proposed framework allows detection of multi-hand instances and localization of hand joints simultaneously. Our experiments show that our method is superior to existing methods.
机译:我们提出了一种基于图片结构(PS)模型的新颖框架,用于根据深度图像估算2D多手姿势。大多数现有的单手姿势估计算法都可能有很强的假设,或者依赖于弱的检测器来检测人的手。我们利用Mask R-CNN来避免上述两个约束。所提出的框架允许同时检测多手实例和手关节的定位。我们的实验表明,我们的方法优于现有方法。

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