System and method for human detection and counting using background modeling, HOG and Haar features
US9001199B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 15, 2011 |
| Grant date | Apr 7, 2015 |
| Priority date | — |
| Expiry date | Feb 5, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V40/103
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system for adaptive learning based human detection for channel input of captured human image signals, the system comprising: a sensor for tracking real-time images of an environment of interest; a feature extraction and classifiers generation processor for extracting a plurality of features and classifying the features associated with time-space descriptors of image comprising background modeling, Histogram of Oriented Gradients (HOG) and Haar like wavelet; a processor configured to process extracted feature classifiers associated with plurality of real-time images; combine the plurality of feature classifiers of time-space descriptors; evaluate a linear probability of human detection based on a predetermined threshold value of the feature classifiers in a time window having at least one image frame; a counter for counting the number of humans in the real-time images; and a transmission device configured to send the final human detection decision and number thereof to a storage device.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.