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NTU Dataset

The NTU dataset is a multi‑video collection that records 60 different human actions, each captured by three cameras from distinct viewpoints. The data files contain per‑frame skeletal coordinates.

Updated 7/24/2020
github

Description

NTU Dataset Overview

Dataset Description

The NTU dataset is a collection of videos covering a wide range of human actions. Each action was recorded using three cameras.

List of Recorded Actions

  1. Drinking water
  2. Eating/snacking
  3. Brushing teeth
  4. Combing hair
  5. Dropping objects
  6. Picking up objects
  7. Throwing
  8. Sitting down
  9. Standing up from a seated position
  10. Clapping
  11. Reading
  12. Writing
  13. Tearing paper
  14. Putting on a jacket
  15. Removing a jacket
  16. Putting on shoes
  17. Removing shoes
  18. Wearing glasses
  19. Taking off glasses
  20. Wearing a hat/cap
  21. Removing a hat/cap
  22. Cheering
  23. Waving
  24. Kicking something
  25. Putting something into a pocket / taking something out of a pocket
  26. Jumping on one foot
  27. Jumping
  28. Making a phone call / answering a phone call
  29. Using a phone/tablet
  30. Typing on a keyboard
  31. Pointing with a finger
  32. Taking a selfie
  33. Checking the time (from a watch)
  34. Rubbing hands
  35. Nodding / bowing
  36. Shaking head
  37. Rubbing face
  38. Saluting
  39. Pressing palms together
  40. Crossing hands in front (signifying stop)
  41. Sneezing / coughing
  42. Staggering
  43. Falling down
  44. Touching head (headache)
  45. Touching chest (stomachache/heart pain)
  46. Touching back (back pain)
  47. Touching neck (neck pain)
  48. Nausea or vomiting
  49. Using a fan (hand or paper) / feeling hot
  50. Hitting / slapping someone
  51. Kicking someone
  52. Pushing someone
  53. Patting someone's back
  54. Pointing at someone with a finger
  55. Hugging someone
  56. Giving something to someone
  57. Touching someone's pocket
  58. Shaking hands
  59. Walking towards each other
  60. Walking away from each other

File Naming Convention

Each file is named according to the following information:

  • Setup number
  • Camera ID
  • Performer ID
  • Replication number
  • Action class label

File Content

Each file contains per‑frame skeletal coordinates. The first three columns of coordinates are retained in the code for training neural networks.

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Topics

Action Recognition
Computer Vision

Source

Organization: github

Created: 7/24/2020

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