This contribution relates to the activities of the TC-19 on “Imaging Signals and Systems.” In a rapidly changing global economy, experiencing an unparalleled integration of science and technology, the development of efficient imaging systems is of extreme significance. The scope of TC-19 is to exchange and disseminate knowledge as well as bridge multidisciplinary areas leading to the creation of new knowledge and establish global collaborative multidisciplinary opportunities by tightening collaborations among government, industry, academia, and healthcare industry. The Committee explores a variety of computer vision and visualization systems spanning from medical imaging to defense, industry, and consumer electronics. These imaging systems use statistical or sophisticated artificial algorithms and require the integration of several technological and computational disciplines, such as detector physics and phenomenology, calibration, metrology, data acquisition, data analysis, image processing, feature extraction, and classification. Often, coexisting competing design requirements and trade-off introduce significant challenges to the design of imaging technologies. For instance, Autonomous Vehicles (AV)s, Unmanned Aerial Vehicles (UAV)s, Unmanned Underwater Vehicle (UUV)s, microsatellites, nanosatellites, and picosatellites for defense and civilian applications are characteristic examples with trade-off between design requirements for high performance imaging and maintaining low-power consumption, high-data transmission, low storage and memory, and reduced payload. To address these competing design challenges, TC-19 introduced the polarimetric neuromorphic vision principles which blend bioinspired principles such as human cognition with the vision of certain arthropods, and aquatic biological species.

中文翻译：

---

偏振动态视觉传感器 p(DVS) 原理

该贡献与 TC-19 关于“成像信号和系统”的活动有关。在瞬息万变的全球经济中，经历着前所未有的科技融合，开发高效的成像系统具有极其重要的意义。TC-19 的范围是交流和传播知识，并通过加强政府、行业、学术界和医疗保健行业之间的合作，在多学科领域建立桥梁，从而创造新知识，并建立全球多学科协作机会。该委员会探索了从医学成像到国防、工业和消费电子产品的各种计算机视觉和可视化系统。这些成像系统使用统计或复杂的人工算法，需要集成多个技术和计算学科，例如探测器物理和现象学、校准、计量学、数据采集、数据分析、图像处理、特征提取和分类。通常，并存的竞争设计要求和权衡会给成像技术的设计带来重大挑战。例如，用于国防和民用应用的自主车辆 (AV)、无人驾驶飞行器 (UAV)、无人水下航行器 (UUV)、微型卫星、纳米卫星和皮卫星是典型的例子，在高性能设计要求之间进行权衡成像和保持低功耗，高数据传输，低存储和内存，并减少了有效载荷。为了应对这些相互竞争的设计挑战，TC-19 引入了极化神经形态视觉原则，该原则将人类认知等生物启发原则与某些节肢动物和水生生物物种的视觉相结合。