TechConnect Innovation Program

Multi-Source Multi-Scale Counting in Extremely Dense Crowd Images

UCF Office of Research & Commercialization, FL, United States

TECHNOLOGY SUMMARY

A software algorithm that produces nearly accurate crowd counts from video or still images containing an average of 1,280 people per frame. The algorithm functions with new constraints in multi-scale Markov random field to infer a single count over the entire image.

Primary Application Area: Electronics, Sensors & Communications

Technology Development Status: Proven Manufacturability

Technology Readiness Level: TRL 4

FIGURES OF MERIT

Value Proposition: Existing crowd-counting algorithms cannot distinguish individuals in crowds of hundreds or thousands, resulting in counting errors. The new invention leverages multiple sources of information to compute a more accurate estimate of the number of individuals present in a dense crowd visible from a single image.

SHOWCASE SUMMARY

Organization Type: Academic/Gov Lab

Showcase Booth #: 523

Website: http://tt.research.ucf.edu

GOVT/EXTERNAL FUNDING SOURCES

Government Funding/Support to Date:

Primary Sources of Funding: Federal Grant

Looking for: Development / License Partners