Signal capture is at the forefront of perceiving and understanding the environment; thus, imaging plays a pivotal role in mobile vision. Recent unprecedented progress in artificial intelligence (AI) has shown great potential in the development of advanced mobile platforms with new imaging devices. Traditional imaging systems based on the “capturing images first and processing afterward” mechanism cannot meet this explosive demand. On the other hand, computational imaging (CI) systems are designed to capture high-dimensional data in an encoded manner to provide more information for mobile vision systems. Thanks to AI, CI can now be used in real-life systems by integrating deep learning algorithms into the mobile vision platform to achieve a closed loop of intelligent acquisition, processing, and decision-making, thus leading to the next revolution of mobile vision. Starting from the history of mobile vision using digital cameras, this work first introduces the advancement of CI in diverse applications and then conducts a comprehensive review of current research topics combining CI and AI. Although new-generation mobile platforms, represented by smart mobile phones, have deeply integrated CI and AI for better image acquisition and processing, most mobile vision platforms, such as self-driving cars and drones only loosely connect CI and AI, and are calling for a closer integration. Motivated by this fact, at the end of this work, we propose some potential technologies and disciplines that aid the deep integration of CI and AI and shed light on new directions in the future generation of mobile vision platforms.

中文翻译：

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计算成像和人工智能：移动视觉的下一次革命


信号捕获处于感知和理解环境的最前沿；因此，成像在移动视觉中起着至关重要的作用。最近，人工智能（AI）取得了前所未有的进展，在开发具有新型成像设备的先进移动平台方面显示出了巨大的潜力。传统基于“先采集图像后处理”机制的成像系统无法满足这种爆炸性的需求。另一方面，计算成像（CI）系统旨在以编码方式捕获高维数据，以为移动视觉系统提供更多信息。得益于AI，CI现在可以应用于现实系统中，通过将深度学习算法集成到移动视觉平台中，实现智能采集、处理和决策的闭环，从而引领移动视觉的下一次革命。本文从使用数码相机的移动视觉的历史开始，首先介绍了 CI 在各种应用中的进展，然后对当前 CI 和 AI 相结合的研究主题进行了全面回顾。尽管以智能手机为代表的新一代移动平台已经深度融合了CI和AI，以实现更好的图像采集和处理，但大多数移动视觉平台，例如自动驾驶汽车和无人机，只是松散地连接CI和AI，并呼吁更紧密的融合。受此事实的启发，在这项工作的最后，我们提出了一些潜在的技术和学科，有助于 CI 和 AI 的深度集成，并揭示下一代移动视觉平台的新方向。