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

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Than Le ◽  
Dang Huynh
Keyword(s):  
Deep Learning ◽  
Human Robot Interaction ◽  
Robot Interaction

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。

scholarly journals Video Captioning Based on Both Egocentric and Exocentric Views of Robot Vision for Human-Robot Interaction

2021 ◽  
Author(s):  
Soo-Han Kang ◽  
Ji-Hyeong Han
Keyword(s):  
Deep Learning ◽  
Natural Language ◽  
Vision System ◽  
Robot Vision ◽  
Learning Model ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Video Captioning ◽  
Global Action ◽  
Deep Learning Model

AbstractRobot vision provides the most important information to robots so that they can read the context and interact with human partners successfully. Moreover, to allow humans recognize the robot’s visual understanding during human-robot interaction (HRI), the best way is for the robot to provide an explanation of its understanding in natural language. In this paper, we propose a new approach by which to interpret robot vision from an egocentric standpoint and generate descriptions to explain egocentric videos particularly for HRI. Because robot vision equals to egocentric video on the robot’s side, it contains as much egocentric view information as exocentric view information. Thus, we propose a new dataset, referred to as the global, action, and interaction (GAI) dataset, which consists of egocentric video clips and GAI descriptions in natural language to represent both egocentric and exocentric information. The encoder-decoder based deep learning model is trained based on the GAI dataset and its performance on description generation assessments is evaluated. We also conduct experiments in actual environments to verify whether the GAI dataset and the trained deep learning model can improve a robot vision system

Robot Vision to Audio Description Based on Deep Learning for Effective Human-Robot Interaction

2019 ◽  
Vol 14 (1) ◽  
pp. 22-30
Author(s):  
Dongkeon Park ◽  
◽  
Kyeong-Min Kang ◽  
Jin-Woo Bae ◽  
Ji-Hyeong Han
Keyword(s):  
Deep Learning ◽  
Robot Vision ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Audio Description

scholarly journals Visual Intention Classification by Deep Learning for Gaze-based Human-Robot Interaction

2020 ◽  
Vol 53 (5) ◽  
pp. 750-755
Author(s):  
Lei Shi ◽  
Cosmin Copot ◽  
Steve Vanlanduit
Keyword(s):  
Deep Learning ◽  
Human Robot Interaction ◽  
Robot Interaction

scholarly journals Hands-Free Human-Robot Interaction Using Multimodal Gestures and Deep Learning in Wearable Mixed Reality

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Kyeong-Beom Park ◽  
Sung Ho Choi ◽  
Jae Yeol Lee ◽  
Yalda Ghasemi ◽  
Mustafa Mohammed ◽  
...  
Keyword(s):  
Deep Learning ◽  
Mixed Reality ◽  
Human Robot Interaction ◽  
Robot Interaction
Sign in / Sign up

Export Citation Format

Share Document