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