互联网服务提供商调整对对象检测的影响
Dara Molloy1,2, Brian Deegan1,2, Darragh Mullins1,2
1School of Engineering, University of Galway, University Road, H91 TK33 Galway, Ireland.
Journal of imaging
|December 22, 2023
概括
改变摄像头中的图像信号处理器 (ISP) 设置会降低高级驾驶辅助系统 (ADAS) 的对象检测性能. 这项研究揭示了不同的ISP参数对模型灵敏度的影响,建议数据增强以提高稳定性.
科学领域:
- 计算机视觉 计算机视觉
- 自主系统 自主系统
- 机器学习 机器学习
背景情况:
- 基于摄像头的物体检测对于先进的驾驶辅助系统 (ADAS) 和自动驾驶汽车至关重要.
- 图像信号处理器 (ISP) 调整为人类的感知,主观的参数选择影响图像质量.
- 在深度学习对象检测模型上,ISP参数变化的性能影响仍然不清楚.
研究的目的:
- 分析图像信号处理器 (ISP) 参数变化对ADAS中使用的物体检测模型的影响.
- 调查流行物体检测模型对八个关键ISP块变化的敏感性.
- 提出一种方法来提高对象检测模型对ISP变异的稳定性.
主要方法:
- 在PASCALRAW和自定义ADAS原始数据集中评估了14个对象检测模型.
- 在八个ISP块中系统地改变了参数:demosaicing,gamma,denoising,边缘增强,局部色调映射,和,对比度和色调角.
- 开发了一种基于ISP参数变化的新型数据增强方法.
主要成果:
- 与默认ISP设置的偏差通常会降低对象检测性能.
- 不同的物体检测模型对ISP参数变化表现出不同程度的灵敏度.
- 拟议的ISP变异数据增强技术提高了模型的稳定性.
结论:
- 互联网服务提供商的参数调整显著影响基于摄像头的对象检测对ADAS.
- 了解模型对ISP变化的敏感性对于可靠的自主系统至关重要.
- 使用ISP变异的数据增强提供了一个有前途的方法来提高对象检测模型的稳定性.
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