1. John Burnum working under Salman Khokhar
Crowd State Analysis
John Burnum working under Salman Khokhar

2. Idea
Analyze surveillance video of crowd motion to construct a scene containing: · predictions of dangerous regions due to crowd density · patterns of crowd motion to predict increased density in those regions

3. Current Method
Calculate optical flow. Analyze to find patterns as in [1] and apply a pattern identifier as in [2] to find regions of convergent or divergent flow – they signify bottlenecks which could be dangerous.
Using patterns, build a scene model which allows us to make some predictions about traffic flow. Mahdi has a paper which will provide an alternative method.
[1] “Scene Understanding by Statistical Modeling of Motion Patterns.” [2] “Similarity Invariant Classification of Events by KL Divergence Minimization.”

4. Initial Results on Patterns from Optical Flow:

5. Results on Patterns from Trajectories:

6. Next Steps:
Continue running current pattern codes with varying parameters to try for better results. Explore modifications to the algorithm or code to improve performance.
Explore alternative options.

7. [1] “Scene Understanding by Statistical Modeling of Motion Patterns
[1] “Scene Understanding by Statistical Modeling of Motion Patterns.” Imran Saleemi, Lance Hartung, and Mubarak Shah. University of Central Florida and University of Wisconsin-Madison.
[2] “Similarity Invariant Classification of Events by KL Divergence Minimization.” Salman Khokhar, Imran Saleemi and Mubarak Shah. University of Central Florida.