Learning classifiers using combined boosting and weight trimming
US7890443B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 13, 2007 |
| Grant date | Feb 15, 2011 |
| Priority date | — |
| Expiry date | Jul 23, 2029 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/774
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A “Classifier Trainer” trains a combination classifier for detecting specific objects in signals (e.g., faces in images, words in speech, patterns in signals, etc.). In one embodiment “multiple instance pruning” (MIP) is introduced for training weak classifiers or “features” of the combination classifier. Specifically, a trained combination classifier and associated final threshold for setting false positive/negative operating points are combined with learned intermediate rejection thresholds to construct the combination classifier. Rejection thresholds are learned using a pruning process which ensures that objects detected by the original combination classifier are also detected by the combination classifier, thereby guaranteeing the same detection rate on the training set after pruning. The only parameter required throughout training is a target detection rate for the final cascade system. In additional embodiments, combination classifiers are trained using various combinations of weight trimming, bootstrapping, and a weak classifier termed a “fat stump” classifier.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.