1. Silvino Barreiros

2. Team all on the same page Initial System Complete Bootstrapping – Research and Coding Started

3. Pos. ID PFA centers bow testing Airplane_flying 70.00% 10.00% 7 / 12 55 / 90 10 / 10 Boat_Ship 80.00% 20.00% 12 / 12 90 / 90 10 / 10 Bridge 60.00% 50.00% 12 / 12 90 / 90 10 / 10 Bus 50.00% 30.00% 7 / 12 55 / 90 10 / 10 Chair 80.00% 40.00% 12 / 12 90 / 90 10 / 10 Cityscape 60.00% 40.00% 12 / 12 90 / 90 10 / 10 Classroom 60.00% 40.00% 12 / 12 90 / 90 10 / 10 Demonstration_Or_Protest80.00% 30.00% 12 / 12 90 / 90 10 / 10 Dog 60.00% 70.00% 12 / 12 90 / 90 10 / 10 Doorway 90.00% 30.00% 12 / 12 90 / 90 10 / 10 Driver 60.00% 30.00% 12 / 12 90 / 90 10 / 10 Emergency_Vehicle 50.00% 20.00% 4 / 12 37 / 90 10 / 10 Female-human-face-closeup 80.00% 10.00% 12 / 12 90 / 90 10 / 10 Flower 60.00% 40.00% 12 / 12 90 / 90 10 / 10 Hand 90.00% 40.00% 12 / 12 90 / 90 10 / 10 Harbor 90.00% 30.00% 12 / 12 90 / 90 10 / 10 Infant 80.00% 10.00% 12 / 12 90 / 90 10 / 10 Kitchen 50.00% 60.00% 12 / 12 90 / 90 10 / 10 Mountain 60.00% 30.00% 12 / 12 90 / 90 10 / 10 Nighttime 90.00% 40.00% 12 / 12 90 / 90 10 / 10 People-dancing 60.00% 20.00% 12 / 12 90 / 90 10 / 10 Person-applauding 40.00% 40.00% 12 / 12 90 / 90 10 / 10 Person-eating 80.00% 50.00% 12 / 12 90 / 90 10 / 10

4. Harbor Curve

5. Mountain ROC Curve

6. Bootstrapping Moving descriptors – High False Alarm Test -> Train Hopefully this will lower PFA (Probability of False Alarms) PFA will lower and PD will stay the same Things to consider The probability to move a descriptor How many to move

7. Finish Bootstrapping and compare results Start looking more at motion implementation Annotating