Human Detection, Tracking and Segmentation in Surveillance Video

Human Detection, Tracking and Segmentation in Surveillance Video

UCF CRCV via YouTube Direct link

Summary

42 of 45

42 of 45

Summary

Class Central Classrooms beta

YouTube videos curated by Class Central.

Classroom Contents

Human Detection, Tracking and Segmentation in Surveillance Video

Automatically move to the next video in the Classroom when playback concludes

  1. 1 Motivation
  2. 2 Video Surveillance Tasks
  3. 3 Outline
  4. 4 Problems
  5. 5 Initial Detection
  6. 6 Training and Classification
  7. 7 Iteratively Learning
  8. 8 Superpixel Segmentation
  9. 9 Bag-of-Words
  10. 10 Qualitative Results
  11. 11 From Detection to Tracking
  12. 12 Part-based Model in Tracking
  13. 13 Features and Classifiers
  14. 14 Data Association
  15. 15 Proposed Method
  16. 16 DPM with Occlusion Handling
  17. 17 Occlusion handling Results
  18. 18 Occlusion Handling in Tracking
  19. 19 Occlusion Reasoning Results
  20. 20 Quantitative Results -- Town Center
  21. 21 Boston Airport
  22. 22 Parking Lot 1
  23. 23 Parking Lot dataset
  24. 24 From Detection to Segmentation
  25. 25 Human Detection
  26. 26 Background Gaussian Mixture Model (GMM)
  27. 27 Part-based Detection Potential
  28. 28 Graph Optimization
  29. 29 Initial Results
  30. 30 Multi-frame Segmentation
  31. 31 Obtaining Tracklets
  32. 32 Multi-frame CRF Optimization
  33. 33 Datasets and Groundtruth
  34. 34 Comparison with Background Subtraction
  35. 35 Segmentation Results (by frame)
  36. 36 For Real-World Application
  37. 37 Objective: Tracking
  38. 38 Multi-threaded Implementation
  39. 39 Tracking Overview
  40. 40 Adaptive Scaling
  41. 41 Local Frame Differencing
  42. 42 Summary
  43. 43 Dissertation Conclusion
  44. 44 Future Work
  45. 45 Publication

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.