1. Surveillance Group Weekly Report
2/7/2007

2. RECAP

3. Detection of People Carrying Objects Using Silhouettes
Larry Davis . PAMI, 2000 and Computer Vision and Image Understanding, 2001
Silhouettes if humans are typically close to symmetric.
We can use symmetry analysis to help us detect when a person is carrying an object.
Davis et al . PAMI, 2000
Mainly true while standing, walking or runing
Davis et al . PAMI, 2000

4. Review

5. Symmetry Analysis
Every pixel of a blob is classified as symmetric or asymmetric : if
X =
Symmetric
Asymmetric
Otherwise
We can analyise how symmetric this blob is.

6. Symmetry Analysis
Person is carrying object if :
Too Simple!

7. Omar’s Approach Recurrent Motion Image (RMI)
Omar Javed and Mubarak Shah, “Tracking And Object Classification For Automated Surveillance”, 2002.
Recurrent Motion Image (RMI)
Binary silhouette image
Binary image indicating areas of motion
High RMI values indicate areas where motion occurs repeatedly

8. Testing
Output blobs
Frame:

9. Testing (Continued) Recurrent Motion Image:
Red areas indicate an RMI above a threshold
Blue areas indicate low RMI values

10. Testing (Continued) if X = Symmetric Asymmetric Otherwise
Perform PCA to find major axis (using low RMI areas)
Perform symmetry analysis disregarding high RMI areas (Red) if
X =
Symmetric
Asymmetric
Otherwise
Asymmetric areas are marked in yellow:

11. PETS 2006 Benchmark Data Dataset S1 (Take 1-C):
People carrying luggage
People leaving luggage