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Accurate and efficient 3D hand pose regression for robot hand teleoperation using a monocular RGB camera
- Source :
- RUA. Repositorio Institucional de la Universidad de Alicante, Universidad de Alicante (UA)
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- In this paper, we present a novel deep learning-based architecture, which is under the scope of expert and intelligent systems, to perform accurate real-time tridimensional hand pose estimation using a single RGB frame as an input, so there is no need to use multiple cameras or points of view, or RGB-D devices. The proposed pipeline is composed of two convolutional neural network architectures. The first one is in charge of detecting the hand in the image. The second one is able to accurately infer the tridimensional position of the joints retrieving, thus, the full hand pose. To do this, we captured our own large-scale dataset composed of images of hands and the corresponding 3D joints annotations. The proposal achieved a 3D hand pose mean error of below 5 mm on both the proposed dataset and Stereo Hand Pose Tracking Benchmark, which is a public dataset. Our method also outperforms the state-of-the-art methods. We also demonstrate in this paper the application of the proposal to perform a robotic hand teleoperation with high success. This work has been supported by the Spanish Government TIN2016-76515R Grant, supported with Feder funds. This work has also been supported by a Spanish grant for PhD studies ACIF/2017/243
- Subjects :
- 0209 industrial biotechnology
Monocular
business.industry
Computer science
Deep learning
Frame (networking)
General Engineering
Ciencia de la Computación e Inteligencia Artificial
02 engineering and technology
Convolutional neural network
Computer Science Applications
Hand pose estimation
020901 industrial engineering & automation
Artificial Intelligence
Teleoperation
0202 electrical engineering, electronic engineering, information engineering
RGB color model
020201 artificial intelligence & image processing
Computer vision
Robot teleoperation
Artificial intelligence
business
Pose
Subjects
Details
- ISSN :
- 09574174
- Volume :
- 136
- Database :
- OpenAIRE
- Journal :
- Expert Systems with Applications
- Accession number :
- edsair.doi.dedup.....ab0e828ca32ae89cc92656e82736e601