ThermVision-DB:一种合成的LWIR热面数据集,用于保护隐私的热视研究
Muhammad Ali Farooq1, Waseem Shariff1, Peter Corcoran1
1C3I Group, School of Engineering, University of Galway, Ireland.
Data in brief
|February 18, 2026
概括
ThermVision-DB引入了一种合成长波红外 (LWIR) 面部数据集,用于保护隐私的研究. 这个数据集使用生成模型来创建现实的面部热数据,以推进面部分析算法.
科学领域:
- 计算机视觉 计算机视觉
- 生物识别信息 生物识别信息
- 人工智能的人工智能
背景情况:
- 面部分析研究需要多样化的数据集,但隐私问题限制了对真实世界的数据的使用.
- 长波红外 (LWIR) 成像比可见光谱成像提供隐私优势.
- 生成模型可以创建合成数据,但现实主义和控制仍然是挑战.
研究的目的:
- 介绍ThermVision-DB,一个新的合成LWIR面部数据集.
- 支持保护隐私视觉,热感知和多式联络面部分析方面的研究.
- 为面部检测,地标定位,表情识别和头部姿势估计在热域中的算法提供基准.
主要方法:
- 利用生成性扩散模型用于光现实热面部图像和视频序列生成.
- 使用文本到图像调节和视频重定向模块来精确控制身份,姿势和表达.
- 确保了数据多样性与合成成人身份,多个表情 (中立,微笑,眉,惊喜),和头姿势旋转 (yaw,pitch,roll).
主要成果:
- 创建了一个全面的合成LWIR面部数据集 (ThermVision-DB) 与图像和视频格式.
- 包括面部定位,地标检测和每个合成样本的身份注释.
- 验证了合成发电管道的可重复使用性,可扩展性和一致的热外观.
结论:
- ThermVision-DB提供了一个符合隐私的可扩展资源,用于推进面部热分析.
- 该数据集有助于研究合成到现实转移学习和跨频谱数据融合.
- 在非商业许可证下的开放发布促进了可重复性和与现有基准的整合.
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