Visual Analysis of Extremely Dense Crowded Scenes

Visual Analysis of Extremely Dense Crowded Scenes

UCF CRCV via YouTube Direct link

Patches: Interest Points

10 of 46

10 of 46

Patches: Interest Points

Class Central Classrooms beta

YouTube videos curated by Class Central.

Classroom Contents

Visual Analysis of Extremely Dense Crowded Scenes

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

  1. 1 Motivation
  2. 2 Presentation Layout
  3. 3 Key Ideas
  4. 4 Problems
  5. 5 Related Work: Counting by Detection
  6. 6 Related Work: Counting by Regression
  7. 7 Spatial Poisson Counting Process
  8. 8 Patches: Head Detections
  9. 9 Patches: Fourier Analysis
  10. 10 Patches: Interest Points
  11. 11 Patches: Fusion
  12. 12 Images: Multi-scale MRF
  13. 13 Results: Quantitative
  14. 14 Results: Per Patch Analysis
  15. 15 Results: Performance Analysis
  16. 16 Results: Analysis of 10th Group
  17. 17 Localization
  18. 18 Schematic Outline
  19. 19 Search results: Uniform Grid
  20. 20 Finding Representative Templates
  21. 21 Hypotheses Selection
  22. 22 Optimization
  23. 23 Bint Quadratic Programming
  24. 24 Background: Deformable Parts Model
  25. 25 Framework
  26. 26 Scale and Confidence Priors
  27. 27 Intermediate Results
  28. 28 Combination-of-Parts (COP) Detection
  29. 29 Global Occlusion Reasoning
  30. 30 Dataset: UCF-HDDC
  31. 31 Results: Qualitative
  32. 32 Results: Step-wise Improvement
  33. 33 Results: Density based Analysis
  34. 34 Results: Comparison
  35. 35 Results: Failure Cases
  36. 36 Chapter Summary
  37. 37 Queen Detection
  38. 38 Detection of Prominent Individuals
  39. 39 Modeling Crowd Behavior
  40. 40 Neighborhood Motion Concurrence
  41. 41 Tracking: Hierarchical Update
  42. 42 Experiments: Sequences
  43. 43 Quantitative Comparison
  44. 44 Component Contribution
  45. 45 Dissertation Conclusion
  46. 46 Future Work

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.