SBIR Phase I: Development of a midwave infrared plenoptic camera prototype

SBIR 第一阶段：中波红外全光相机原型的开发

• 批准号: 2014933
• 负责人: Eugene Petilli
• 金额: $ 22.5万
• 依托单位: OWL AUTONOMOUS IMAGING INC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-15 至 2021-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2014933&HistoricalAwards=false
• 关键词: SBIR; Phase; Development; midwave; infrared

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to demonstrate the viability of a new camera solution for night or day and in adverse weather. Today's automatic driver assist systems are often inadequate for identifying pedestrians at night or in poor conditions. This project will demonstrate a camera solution that will operate day and night, in all weather, and detects and classifies pedestrians, cyclists, animals as well as vehicles (either moving or stationary), thereby unlocking safer vehicle operation and saving lives.This Small Business Innovation Research (SBIR) Phase I project addresses a shortcoming of contemporary autonomous vehicle sensors by introducing a high-resolution 3D sensor that performs well in any lighting condition and most weather conditions. The research builds upon light field, or plenoptic, technologies proven effective in the visible domain and applies them to the thermal domain with additional innovations. A purpose-built microlens array (MLA) is coupled with a mid-wave infrared (MWIR) camera and new thermal computational photogrammetry algorithms to deliver dense 2D and range information with sufficient detail to quickly classify surrounding objects. In particular, it will be shown that 3D MWIR video is ideally suited to readily detect and classify objects that may move such as pedestrians, vehicles and animals.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该小型企业创新研究 (SBIR) 第一阶段项目的更广泛影响/商业潜力是展示新型摄像头解决方案在夜间或白天以及恶劣天气下的可行性。当今的自动驾驶辅助系统通常不足以在夜间或恶劣条件下识别行人。 该项目将展示一种摄像头解决方案，该解决方案可以在任何天气条件下昼夜运行，对行人、骑自行车的人、动物以及车辆（移动或静止）进行检测和分类，从而使车辆操作更安全并拯救生命。这个小型企业创新研究 (SBIR) 第一阶段项目通过引入在任何照明条件下都表现良好的高分辨率 3D 传感器来解决当代自动驾驶车辆传感器的缺点。 大多数天气条件。该研究建立在光场或全光技术的基础上，这些技术在可见光领域被证明是有效的，并将其通过额外的创新应用于热领域。专用微透镜阵列 (MLA) 与中波红外 (MWIR) 相机和新的热计算摄影测量算法相结合，可提供密集的 2D 和距离信息以及足够的细节，以快速对周围物体进行分类。特别是，它将证明 3D MWIR 视频非常适合轻松检测和分类可能移动的物体，如行人、车辆和动物。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。