Liquid crystal polarization camera

Abstract

We present a fully automated system which unites CCD camera technology with liquid crystal technology to create a polarization camera capable of sensing the partial linear polarization of reflected light from objects at pixel resolution. As polarization sensing not only measures intensity but also additional physical parameters of light, it can therefore provide a richer set of descriptive physical constraints for the understanding of images. Previously it has been shown that polarization cues can be used to perform dielectric/metal material identification, specular and diffuse reflection component analysis, as well as complex image segmentations that would be significantly more complicated or even infeasible using intensity and color alone. Such analysis has so far been done with a linear polarizer mechanically rotated in front of a CCD camera. The full automation of resolving polarization components using liquid crystals not only affords an elegant application, but significantly speeds up the sensing of polarization components and reduces the amount of optical distortion present in the wobbling of a mechanically rotating polarizer. In our system two twisted nematic liquid crystals are placed in front of a fixed linear polarizer placed in front of a CCD camera. The application of a series of electrical pulses to the liquid crystals in synchronization with the CCD camera video frame rate produces a controlled sequence of polarization component images that are stored and processed on Datacube boards. We present a scheme for mapping a partial linear polarization state measured at a pixel into hue, saturation and intensity producing a representation for a partial linear polarization image. Our polarization camera currently senses partial linear polarization and outputs such a color representation image at 5 Hz. The unique vision understanding capabilities of our polarization camera system are demonstrated with experimental results showing polarization-based dielectric/metal material classification, specular reflection and occluding contour segmentations in a fairly complex scene, and surface orientation constraints.