Polarization information of the light can provide rich cues for computer vision and scene understanding tasks, such as the type of material, pose, and shape of the objects. With the advent of new and cheap polarimetric sensors, this imaging modality is becoming accessible to a wider public for solving problems such as pose estimation, 3D reconstruction, underwater navigation, and depth estimation. However, we observe several limitations regarding the usage of this sensorial modality, as well as a lack of standards and publicly available tools to analyze polarization images. Furthermore, although polarization camera manufacturers usually provide acquisition tools to interface with their cameras, they rarely include processing algorithms that make use of the polarization information. In this paper, we review recent advances in applications that involve polarization imaging, including a comprehensive survey of recent advances on polarization for vision and robotics perception tasks. We also introduce a complete software toolkit that provides common standards to communicate with and process information from most of the existing micro-grid polarization cameras on the market. The toolkit also implements several image processing algorithms for this modality, and it is publicly available on GitHub: https://github.com/vibot-lab/Pola4all_JEI_2023.

翻译：摘要：光的偏振信息可为计算机视觉与场景理解任务提供丰富线索，例如物体材质、姿态和形状。随着新型低成本偏振传感器的出现，这种成像模式正被更广泛的受众用于解决姿态估计、三维重建、水下导航和深度估计等问题。然而，我们观察到该传感模式的使用存在若干局限，同时缺乏偏振图像分析的标准化流程和公开工具。此外，尽管偏振相机厂商通常提供配套的采集工具，但很少包含利用偏振信息的处理算法。本文回顾了涉及偏振成像应用的最新进展，包括对偏振在视觉与机器人感知任务中前沿研究的全面综述。我们还介绍了一个完整的软件工具包，该工具包提供了与市场上大多数现有微网格偏振相机通信并处理其信息的通用标准，同时实现了针对该成像模式的多种图像处理算法。该工具包已在GitHub上公开获取：https://github.com/vibot-lab/Pola4all_JEI_2023。