Skip to content

Dynamic gesture dataset, can be used for interaction between human and robots

Notifications You must be signed in to change notification settings

DanielC-MST/Dynamic-gesture-dataset-MHI-

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

17 Commits
 
 
 
 
 
 

Repository files navigation

Motion History Image dataset of ten designed dynamic gestures

Motion History Image dataset of ten designed dynamic gestures, can be used for interaction between human and robots

IMECE 2020 conference paper

ISFA 2020 conference paper

Design of 10 dynamic gestures:

image

Motion Hisory Extraction

Motion History Image (MHI) is is a static image template helps in understanding the motion location and path as it progresses.

image

Motion History Image (MHI) Dataset

In the Dataset, i.e. "Dataset_MHI_of_Ten_Dynamic_Gesture.zip", there are MHIs of the above ten dynamic gestures.

  1. All images are named based on the sequence of the gesture and MHI figure above.
  2. The size of the each MHI data had been resize as 32 * 32, which is easier for the deep learning training.

image

  1. Four different data augmentation methods were used in this dataset, including brightness change, shift, zooming, and perspective transformation, as shown below:

image

Reference

In the file "Dataset_MHI_of_Ten_Dynamic_Gestures"

  1. “Design of a Real-Time Human-Robot Collaboration System Operated by Dynamic Gestures,” H. Chen, M. C. Leu, W. Tao and Z. Yin, Proceedings of the ASME 2020 International Mechanical Engineering Congress and Exposition (IMECE 2020), November 13-19, 2020, Portland, OR.

  2. “Dynamic Gesture Design and Recognition for Human-Robot Collaboration with Convolutional Neural Networks,” H. Chen, W. Tao, M. C. Leu, and Z. Yin, Proceedings of the 2020 International Symposium on Flexible Automation (ISFA 2020), Jul. 5-9, 2020, Chicago, IL.

  3. “An Integrated Target Acquisition Approach and Graphical User Interface Tool for Parallel Manipulator Assembly,” H. Chen, Z. Teng, Z. Guo, and P. Zhao, ASME Journal of Computing and Information Science in Engineering, Vol. 20, No. 2, 2020.

  4. “Design of a Robotic Rehabilitation System for Mild Cognitive Impairment Based on Computer Vision”. H. Chen, H. Zhu, Z. Teng, and P. Zhao, 2020. ASME Journal of Engineering and Science in Medical Diagnostics and Therapy, Vol. 3, No. 2, 2020.

Releases

No releases published

Packages