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Efficient Human-Robot Interaction using Deep Learning with Mask R-CNN: Detection, Recognition, Tracking and Segmentation

Than Le, Dang Huynh

Abstract

我们
通过提出深度神经网络与
机械机器人系统的集成来解决社会人机交互问题,使其对人机
交互活动具有鲁棒性。掩模R-CNN是一种用于物体
检测的神经网络,可以有效地帮助定位可以
被操纵以指示机器人头部运动的人脸。我们的
方法不仅适用于检测和分割
任务,而且能够与
表示3D尺寸的并行微型机械手的机制
,工作空间的位置和方向集成。它还可以解决
目标分割问题,这似乎是
当今计算机视觉中最具挑战性的问题之一。


Keywords

Human robot interaction; deep neural net- work; tracking robotics; detection; mini-parallel kinematic.

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DOI: http://dx.doi.org/10.18063/phci.v1i2.783
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