Extended monocular 3D imaging via the fusion of diffraction- and polarization-based depth cues

3D vision is of paramount importance for numerous applications ranging from machine intelligence to precision metrology. Despite much recent progress, the majority of 3D imaging hardware remains bulky and complicated and provides much lower image resolution compared to its 2D counterparts. Moreover, there are many well-known scenarios where existing 3D imaging solutions frequently fail. Here, we introduce an extended monocular 3D imaging (EM3D) framework that exploits the multi-stage fusion of diffraction- and polarization-based depth cues. By using a compact monocular camera equipped with a diffractive–refractive hybrid lens and a commercial polarization sensor, we experimentally demonstrate the snapshot acquisition of a million-pixel and accurate 3D point cloud for extended scenes that are traditionally challenging, including those with low texture, high complexity, high reflectivity, or near transparency, without prior data. Furthermore, we discover that the combination of depth and polarization information can unlock unique opportunities for distinguishing objects by their material properties, which facilitate applications like target recognition and face anti-spoofing. The expanded machine vision in a minimal form factor may allow the deployment of monocular cameras for applications in much more diverse scenarios.