基于场景和人感知的虚拟组合摄影
Zhenquan Shi1, Hongming Lu2,3, Xinyue Sun2
1School of Software Engineering, Tiangong University, Tianjin, China.
Heliyon
|January 8, 2024
概括
这项研究引入了一个虚拟组合摄影模型,以现实的方式将失踪人员添加到组合照片中. 该方法考虑了个人属性和真实虚拟人合成的背景.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 计算机视觉 计算机视觉
背景情况:
- 团体照片对于记录事件至关重要.
- 现有的添加人群照片的方法往往缺乏现实性.
- 当前的方法无法整合个体特征,如身高和身体形状,或者同时考虑姿势和边界.
研究的目的:
- 开发一个新的虚拟组合摄影模型.
- 为了增强合成个体成组合照片的现实主义和真实性.
- 通过结合个别属性来解决当前上下文预测模型的局限性.
主要方法:
- 提出了一个两阶段的虚拟组合摄影模型.
- 阶段1:使用全球背景和目标人特征预测个人属性 (位置,姿势,边界).
- 阶段2:根据预测的姿势和边界信息生成新的组合照片.
主要成果:
- 提出的方法显著提高了组合照片中合成个体的和性和真实性.
- 该模型成功地合成了应该在组中存在的个体.
- 实验结果表明,在虚拟组合照片组合中表现优越.
结论:
- 虚拟组合摄影模型有效地结合了全球背景和个人属性.
- 这种方法为创建与缺席个体的现实集体照片提供了重大进展.
- 这种方法非常适合在虚拟组合摄影和图像合成中的应用.
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