Learning method and learning device for object detector based on CNN to be used for multi-camera or surround view monitoring using image concatenation and target object merging network, and testing method and testing device using the same
US10423860B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 22, 2019 |
| Grant date | Sep 24, 2019 |
| Priority date | — |
| Expiry date | Jan 22, 2039 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04N7/181
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
A method for learning parameters of an object detector based on a CNN adaptable to customers' requirements such as KPI by using an image concatenation and a target object merging network is provided. The CNN can be redesigned when scales of objects change as a focal length or a resolution changes depending on the KPI. The method includes steps of: a learning device instructing an image-manipulating network to generate n manipulated images; instructing an RPN to generate first to n-th object proposals respectively in the manipulated images, and instructing an FC layer to generate first to n-th object detection information; and instructing the target object merging network to merge the object proposals and merge the object detection information. In this method, the object proposals can be generated by using lidar. The method can be useful for multi-camera, SVM(surround view monitor), and the like, as accuracy of 2D bounding boxes improves.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.