STTR Phase I: FlatCam: Inexpensive, Compact Lensless Cameras for IoT Applications

这一小型企业技术转移(STTR)第一阶段项目的更广泛影响是开发了一种新的成像平台技术，该技术有可能影响许多领域，包括消费者成像、医学成像、光谱学、天文学、监视和国防。将这项技术转化为实际应用将意味着这项技术可以用于个性化体验、提高生活质量和增强安全性。STTR第一阶段提议的项目将开发廉价的无镜头成像设备(与当前最先进的相机相反，这些相机依赖镜头形成聚焦图像)，可以与物联网(IoT)设备集成以收集视觉数据。由于相机中的镜头占成本和重量的绝大部分，这些设备可以在成本上降低数量级，使相机能够集成到更大的家用、汽车和城市规模的智能设备阵列中。该项目的研究任务是：(1)利用优化和机器学习的进步开发快速、实时的图像重建算法(2)开发与无透镜成像平台一起运行的人脸检测、识别和跟踪算法，以实现个性化等物联网应用，以及(3)通过探索端到端系统集成和优化来改善数据通信(有线或无线)，以满足当前和未来的物联网需求。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact of this Small Business Technology Transfer (STTR) Phase I project is the development of a new imaging platform technology that has the potential to affect many areas including consumer imaging, medical imaging, spectroscopy, astronomy, surveillance, and defense. Transitioning this technology into real applications will mean this technology can be used for personalized experiences, improved quality of life, and increased safety.The STTR Phase I proposed project will develop inexpensive, lensless imaging devices (contrary to the current state-of-art cameras, that rely on lenses to form a focused image), that can be integrated with internet-of-things (IoT) devices to gather visual data. Since the lens in a camera accounts for the vast majority of the cost and the weight, these devices can provide order of magnitude reductions in cost, allowing cameras to be integrated into a much larger array of home, auto, and city-scale smart devices. The research tasks in this project are: (1) developing fast, real-time algorithms for image reconstruction exploiting advances in optimization and machine learning (2) developing face detection, recognition, and tracking algorithms that operate with the lensless imaging platform for IoT applications like personalization, and (3) improving data communication (wired or wireless) to meet current and future IoT needs by exploring end-to-end system integration and optimization.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.