Invention Grant
- Patent Title: Machine-learning model, methods and systems for removal of unwanted people from photographs
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Application No.: US17079084Application Date: 2020-10-23
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Publication No.: US11676390B2Publication Date: 2023-06-13
- Inventor: Qiang Tang , Zili Yi , Zhan Xu
- Applicant: Qiang Tang , Zili Yi , Zhan Xu
- Applicant Address: CA Burnaby
- Assignee: Huawei Technologies Co., Ltd.
- Current Assignee: Huawei Technologies Co., Ltd.
- Current Assignee Address: CN Shenzhen
- Main IPC: G06V20/52
- IPC: G06V20/52 ; G06T7/11 ; G06V40/16

Abstract:
Methods and systems for fully-automatic image processing to detect and remove unwanted people from a digital image of a photograph. The system includes the following modules: 1) Deep neural network (DNN)-based module for object segmentation and head pose estimation; 2) classification (or grouping) of wanted versus unwanted people based on information collected in the first module; 3) image inpainting of the unwanted people in the digital image. The classification module can be rules-based in an example. In an example, the DNN-based module generates, from the digital image: 1. A list of object category labels, 2. A list of object scores, 3. A list of binary masks, 4. A list of object bounding boxes, 5. A list of crowd instances, 6. A list of human head bounding boxes, and 7. A list of head poses (e.g., yaws, pitches, and rolls).
Public/Granted literature
- US20220129682A1 MACHINE-LEARNING MODEL, METHODS AND SYSTEMS FOR REMOVAL OF UNWANTED PEOPLE FROM PHOTOGRAPHS Public/Granted day:2022-04-28
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