Face detection using small-scale convolutional neural network (CNN) modules for embedded systems
US10268947B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 21, 2017 |
| Grant date | Apr 23, 2019 |
| Priority date | — |
| Expiry date | Jul 21, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V40/178
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments described herein provide various examples of a face detection system, based on using a small-scale hardware convolutional neural network (CNN) module configured into a multi-task cascaded CNN. In some embodiments, a subimage-based CNN system can be configured to be equivalent to a large-scale CNN that processes the entire input image without partitioning such that the output of the subimage-based CNN system can be exactly identical to the output of the large-scale CNN. Based on this observation, some embodiments of this patent disclosure make use of the subimage-based CNN system and technique on one or more stages of a cascaded CNN or a multitask cascaded CNN (MTCNN) so that a larger input image to a given stage of the cascaded CNN or the MTCNN can be partitioned into a set of subimages of a smaller size. As a result, each stage of the cascaded CNN or the MTCNN can use the same small-scale hardware CNN module that is associated with a maximum input image size constraint.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.