Title:
ディープネットワークを使用する自動オブジェクトアノテーションのための方法およびシステム
Document Type and Number:
Japanese Patent JP6932159
Kind Code:
B2
Abstract:
Object annotation is images is tedious time consuming task when large volume of data needs to annotated. Existing methods limit to semiautomatic approaches for annotation. The embodiments herein provide a method and system for a deep network based architecture for automatic object annotation. The deep network utilized is a two stage network with first stage as an annotation model comprising a Faster Region-based Fully Convolutional Networks (F-RCNN) and Region-based Fully Convolutional Networks (RFCN) providing for two class classification to generate annotated images from a set of single object test images. Further, the newly annotated test object images are then used to synthetically generate cluttered images and their corresponding annotations, which are used to train the second stage of the deep network comprising the multi-class object detection/classification model designed using the F-RCNN and the RFCN as base networks to automatically annotate input test image in real time.
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Inventors:
Chandan Kumar Singh
Anima Majumuda
Swagat Kumar
Laxmidar Behera
Anima Majumuda
Swagat Kumar
Laxmidar Behera
Application Number:
JP2019126832A
Publication Date:
September 08, 2021
Filing Date:
July 08, 2019
Export Citation:
Assignee:
Tata Consultancy Services Limited
International Classes:
G06T7/00; G06N3/04; G06N3/08; G06T1/40; G06T3/00; G06V10/776
Other References:
Samet Akcay, et al.,An evaluation of region based object detection strategies within X-ray baggage security imagery,2017 IEEE International Conference on Image Processing (ICIP),2017年 9月20日,pp.1337-1341,URL,https://ieeexplore.ieee.org/document/8296499
HyunJun Jo, et al.,Data augmentation using synthesized images for object detection,2017 17th International Conference on Control, Automation and Systems (ICCAS),2017年12月21日,pp.1035-1038,URL,https://ieeexplore.ieee.org/document/8204369
HyunJun Jo, et al.,Data augmentation using synthesized images for object detection,2017 17th International Conference on Control, Automation and Systems (ICCAS),2017年12月21日,pp.1035-1038,URL,https://ieeexplore.ieee.org/document/8204369
Attorney, Agent or Firm:
Yasuhiko Murayama
Shinya Mitsuhiro
Tatsuhiko Abe
Shinya Mitsuhiro
Tatsuhiko Abe