Title:
FINE-GRAINED OBJECT RECOGNITION IN ROBOTIC SYSTEMS
Document Type and Number:
WIPO Patent Application WO/2018/157873
Kind Code:
A1
Abstract:
A method for fine-grained object recognition in a robotic system is disclosed that includes obtaining an image of an object from an imaging device. Based on the image, a deep category-level detection neural network is used to detect pre-defined categories of objects. A feature map is generated for each pre-defined category of object detected by the deep category-level detection neural network. Embedded features are generated, based on the feature map, using a deep instance-level detection neural network corresponding to the pre-defined category of the object, wherein each pre-defined category of an object comprises a corresponding different instance-level detection neural network. An instance-level of the object is determined based on classification of the embedded features.
Inventors:
JIANG WEI (US)
WANG WEI (US)
WANG WEI (US)
Application Number:
PCT/CN2018/078019
Publication Date:
September 07, 2018
Filing Date:
March 05, 2018
Export Citation:
Assignee:
HUAWEI TECH CO LTD (CN)
International Classes:
G06T7/00; G06V10/25; G06V10/764; G06V10/772; G06V10/774; G06V10/141
Foreign References:
| CN106028134A | 2016-10-12 | |||
| CN103955702A | 2014-07-30 | |||
| US5608819A | 1997-03-04 |
Other References:
ZHANG, NING ET AL.: "Part-Based R-CNNs for Fine-Grained Category Detection", COMPUTER VISION - ECCV 2014, vol. 8689, 14 September 2014 (2014-09-14), pages 834 - 849, XP055537908
See also references of EP 3501002A4
See also references of EP 3501002A4
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