OO-dMVMT: A Deep Multi-view Multi-task Classification Framework for Real-time 3D Hand Gesture Classification and Segmentation

Cunico, Federico; Girella, Federico; Avogaro, Andrea; Emporio, Marco; Giachetti, Andrea; Cristani, Marco

doi:10.1109/cvprw59228.2023.00275

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Cited by 3 publications

References 22 publications

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Language-enhanced RNR-Map: Querying Renderable Neural Radiance Field maps with natural language

Taioli,

Cunico,

Girella

et al. 2023

2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)

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Language-enhanced RNR-Map: Querying Renderable Neural Radiance Field maps with natural language

Taioli,

Cunico,

Girella

et al. 2023

2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)

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Demo: gesture based interaction with the Hololens 2

Emporio,

Caputo,

Pintani

et al. 2023

Proceedings of the 15th Biannual Conference of the Italian SIGCHI Chapter

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A Robotic Teleoperation System Enhanced by Augmented Reality for Natural Human–Robot Interaction

Wang,

Guo,

et al. 2024

Cyborg Bionic Syst

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Telekinesis, as commonly portrayed in science fiction literature and cinema, is a super power wherein users control and manipulate objects absent in physical interaction. In real world, enhancing human–robot interaction needs the synthesis of human intuitive processes with robotic arm. This paper introduces a robotic teleoperation system achieving the essence of telekinetic operations, combining the profound capabilities of augmented reality (AR) with the robotic arm operations. Utilizing AR, the proposed methodology offers operators with a visual feedback, facilitating a level of control surpassing the capacities of natural interfaces. By using AR-driven visual recognition, this system achieves operations in a virtual environment, subsequently actualized in the real world through the robotic arm. Through multiple experiments, we found that the system has a small margin of error in telekinesis operations, meeting the needs of remote operation. Furthermore, our system can operate on objects in the real world. These experiments underscore the capability of the remote control system to assist humans in accomplishing a wider range of tasks through the integration of AR and robotic arms, providing a natural human–robot interaction approach.

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OO-dMVMT: A Deep Multi-view Multi-task Classification Framework for Real-time 3D Hand Gesture Classification and Segmentation

Cited by 3 publications

References 22 publications

Language-enhanced RNR-Map: Querying Renderable Neural Radiance Field maps with natural language

Language-enhanced RNR-Map: Querying Renderable Neural Radiance Field maps with natural language

Demo: gesture based interaction with the Hololens 2

A Robotic Teleoperation System Enhanced by Augmented Reality for Natural Human–Robot Interaction

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