3D Face Authentication Software Test Automation
The 3D face authentication has become a hot trend for researchers and developers in the recent years, due to its many advantages over the 2D face recognition feature. The 3D reconstruction of a human face using both near-infrared and depth sensors is a complex process on mobile phones. It commonly i...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9026936/ |
| _version_ | 1818929784153964544 |
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| author | Debdeep Banerjee Kevin Yu |
| author_facet | Debdeep Banerjee Kevin Yu |
| author_sort | Debdeep Banerjee |
| collection | DOAJ |
| description | The 3D face authentication has become a hot trend for researchers and developers in the recent years, due to its many advantages over the 2D face recognition feature. The 3D reconstruction of a human face using both near-infrared and depth sensors is a complex process on mobile phones. It commonly involves algorithms like face detection, face landmark detection, facial feature extraction, and depth information analysis. The 3D face authentication feature is critical for the user as per as security and also providing a convenient way to authenticate by the correct user. Therefore, the testing of 3D face authentication algorithms and applications in terms of functionality, performance, and stability is critical. However, the research on 3D face authentication application level validation and testing method is lacking in the field. Most testers are still validating the application manually. In this paper, we propose a robotic-arm-based test automation for testing the 3D face authentication feature on mobile phones. We programmed a 6 degree of freedom (6-DOF) robotic arm to perform 3D face authentication automated tests that were executed manually before. Our test automation also benchmarked the performance of an in-house developed 3D face authentication application and a 3<sup>rd</sup> party application which yielded promising latency and accuracy comparison results under different performance-impacting test scenarios. |
| first_indexed | 2024-12-20T03:50:18Z |
| format | Article |
| id | doaj.art-4a6792fad3564727ac98a629bd4c26b3 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T03:50:18Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-4a6792fad3564727ac98a629bd4c26b32022-12-21T19:54:28ZengIEEEIEEE Access2169-35362020-01-018465464655810.1109/ACCESS.2020.297889990269363D Face Authentication Software Test AutomationDebdeep Banerjee0https://orcid.org/0000-0002-4907-3054Kevin Yu1https://orcid.org/0000-0001-9224-3891Qualcomm Technologies, Inc., San Diego, CA, USAQualcomm Technologies, Inc., San Diego, CA, USAThe 3D face authentication has become a hot trend for researchers and developers in the recent years, due to its many advantages over the 2D face recognition feature. The 3D reconstruction of a human face using both near-infrared and depth sensors is a complex process on mobile phones. It commonly involves algorithms like face detection, face landmark detection, facial feature extraction, and depth information analysis. The 3D face authentication feature is critical for the user as per as security and also providing a convenient way to authenticate by the correct user. Therefore, the testing of 3D face authentication algorithms and applications in terms of functionality, performance, and stability is critical. However, the research on 3D face authentication application level validation and testing method is lacking in the field. Most testers are still validating the application manually. In this paper, we propose a robotic-arm-based test automation for testing the 3D face authentication feature on mobile phones. We programmed a 6 degree of freedom (6-DOF) robotic arm to perform 3D face authentication automated tests that were executed manually before. Our test automation also benchmarked the performance of an in-house developed 3D face authentication application and a 3<sup>rd</sup> party application which yielded promising latency and accuracy comparison results under different performance-impacting test scenarios.https://ieeexplore.ieee.org/document/9026936/Automationroboticssoftware testingsoftware engineering |
| spellingShingle | Debdeep Banerjee Kevin Yu 3D Face Authentication Software Test Automation IEEE Access Automation robotics software testing software engineering |
| title | 3D Face Authentication Software Test Automation |
| title_full | 3D Face Authentication Software Test Automation |
| title_fullStr | 3D Face Authentication Software Test Automation |
| title_full_unstemmed | 3D Face Authentication Software Test Automation |
| title_short | 3D Face Authentication Software Test Automation |
| title_sort | 3d face authentication software test automation |
| topic | Automation robotics software testing software engineering |
| url | https://ieeexplore.ieee.org/document/9026936/ |
| work_keys_str_mv | AT debdeepbanerjee 3dfaceauthenticationsoftwaretestautomation AT kevinyu 3dfaceauthenticationsoftwaretestautomation |