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Andrii Boichuk: Video-based action recognition on edge

  1. VIDEO-BASED ACTION RECOGNITION ON EDGE 01.04.2023
  2. ● How often a senior is treated in emergency room due to a fall? 2
  3. ● How often a senior is treated in emergency room due to a fall? - every 13 minutes 3
  4. ● How often a senior is treated in emergency room due to a fall? - every 13 minutes ● How much money do people spend due to falls? 4
  5. ● How often a senior is treated in emergency room due to a fall? - every 13 minutes ● How much money do people spend due to falls? - 69 billion $ annually 5
  6. 6 Structure What 1 Why 2 How 3 Q&A 4
  7. 7 Who am I? ANDRII BOICHUK Research Engineer ● Lecturer at NU “Lviv Polytechnic” ● 10+ year in IT, 5+ in research ● Tons of research activity
  8. 8 Who am I? (SQUAD Edition) FOLLOW ON FACEBOOK FOLLOW ON LINKEDIN FOLLOW ON INSTAGRAM 1250 + Research Delivery QA Embedded Hardware Mobile Infrastructure Product Design Kyiv Lviv Uzhhorod STREAMS OF TECHNOLOGIES SQUAD – one of the biggest RnD center in Ukraine. SQUAD – has some of the best optical labs in Europe.
  9. ● 500+ студентів ● Вступний бал 190+ ● 50% викладачів з галузі 9 Who am I? (NULP edition) https://aidept.com.ua/
  10. What?
  11. ● Action recognition 11 What is video-based action recognition on edge?
  12. 12 Action recognition Action classification seeks to assign the correct label (e.g. “cooking,” “writing,” etc.) to a given image or video. Action localization, given a particular action and a video as input, seeks to identify the correct location and timestamp in the video when the action is being performed.
  13. ● Action recognition ● Video based 13 What is video-based action recognition on edge?
  14. ● Action recognition ● Video based 14 What is video-based action recognition on edge?
  15. ● Action recognition ● Video based ● On edge 15 What is video-based action recognition on edge?
  16. 16 What is video-based action recognition on edge? ● Action recognition ● Video based ● On edge
  17. Why?
  18. 18 Why action recognition? ● Saves lives
  19. 19 Saves lives
  20. 20 Why action recognition? ● Saves lives ● Saves lives and money
  21. 21 Saves lives and money
  22. 22 Why action recognition? ● Saves lives ● Saves lives and money ● Gives peace of mind
  23. 23 Gives peace of mind Most of the times
  24. 24 Why action recognition? ● Saves lives ● Saves lives and money ● Gives peace of mind ● Saves time
  25. 25 Saves time - sport highlights
  26. 26 Cloud problems ● Privacy
  27. 27 Cloud problems ● Privacy ● “bad internet connection”
  28. 28 Cloud problems ● Privacy ● “bad internet connection” ● Expensive
  29. 29 Cloud problems ● Privacy ● “bad internet connection” ● Expensive ● Streaming latency
  30. 30 Solution? ● Edge!
  31. Why not?
  32. ● Harder 32
  33. ● Harder - HW, optimizations techniques and combinations 33
  34. ● Harder ● Worse accuracy 34
  35. ● Harder ● Worse accuracy ● Uses additional resources which might be needed for other tasks 35
  36. Where?
  37. 37 Where? ● Surveillance cameras
  38. 38 Where
  39. 39 Where? ● Smart home cameras ● Fall detection
  40. 40 Where
  41. How?
  42. 42 How ● Research
  43. 43 How ● Research - always check for SoTA - paperswithcode, github, CVPR, EECV
  44. 44 How ● Research ● Hardware
  45. 45 How ● Research ● Hardware - know your limitations - CPU, GPU, FPGA or SoC?
  46. 46 How ● Research ● Hardware ● Optimizations
  47. 47 How ● Research ● Hardware ● Optimizations - quantization, pruning and hardware independent techniques
  48. 48 How ● Research ● Hardware ● Optimizations
  49. - CNN-based model - GPU as hardware - Pros: high throughput, high performance, no optimizations needed - Cons: memory latency, high energy consumption, might be expensive 49 How
  50. - Transformer-based model - CPU as hardware - Pros: low latency, universal, easy to use and optimize - Cons: mid performance on other stats - mid energy consumption, mid speed 50 How
  51. 51 How ● Research ● Hardware ● Optimizations ● Make your problem as narrow as possible
  52. - Have the most basic baseline ready ASAP - Chose target HW as soon as possible - Go for SoTA 52 Tips
  53. Q&A
  54. Andrii Boichuk Research engineer Thank You! SQUAD IN FACEBOOK SQUAD IN LINKEDIN SQUAD IN INSTAGRAM
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