Object retrieval in video data using complementary detectors
US9002060B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 28, 2012 |
| Grant date | Apr 7, 2015 |
| Priority date | — |
| Expiry date | Jun 15, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/44
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Automatic object retrieval from input video is based on learned, complementary detectors created for each of a plurality of different motionlet clusters. The motionlet clusters are partitioned from a dataset of training vehicle images as a function of determining that vehicles within each of the scenes of the images in each cluster share similar two-dimensional motion direction attributes within their scenes. To train the complementary detectors, a first detector is trained on motion blobs of vehicle objects detected and collected within each of the training dataset vehicle images within the motionlet cluster via a background modeling process; a second detector is trained on each of the training dataset vehicle images within the motionlet cluster that have motion blobs of the vehicle objects but are misclassified by the first detector; and the training repeats until all of the training dataset vehicle images have been eliminated as false positives or correctly classified.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.