Crowd_Count++ Final Presentation Juan Mejia, Rosario Antunez, Michael Safdieh City College of New York

Crowd_Count++ Counting the number of people in images and videos arises in several real world applications including crowd management, design and analysis of buildings and spaces, and safety and security. In certain scenarios such as public rallies, marathons, public parks, and transportation, the number of people in the given scenario is of direct importance. This process usually involves fixed cameras, allowing the use of background modelling and change detection algorithms which produce a change measure at each pixel in a video stream.

Utility Business Insights. CCNY. Safety and Security. Almost any other scenario where crowd counting is applied.

Challenges Making accuracy as high as possible. Background subtraction. Low quality input images.

Solving the Challenges HAARS. Histogram of Oriented Gradients. Non-Maximum Suppression. BackgroundSubtractorMOG. BackgroundSubtractorMOG2. BackgroundSubtractorGMG.

HAARS (Non-Maximum Suppression)

Histogram of Oriented Gradients (Non-Maximum Suppression)

Background Subtraction

Background Subtraction Demo

Website Demo

Future Work / Improvements Make the system more accurate by doing motion detection (similar to kinect). Be able to effectively process very low quality input(first point will help with this). Investigate and possibly implement skin detection. Modifications to frontend.

Questions?

THANK YOU :)