LIQUID-CRYSTAL POLARIZATION CAMERA

We present a fully automated system which unites CCD camera technology with liquid crystal technology to create a polarization camera capabl e of sensing the partial linear polarization of reflected light from o bjects at pixel resolution. As polarization sensing not only measures intensity but also additional physical parameters of light, it can the refore provide a richer set of descriptive physical constraints for th e understanding of images. Recently it has been shown that polarizatio n cues can be used to perform dielectric/metal material identification , specular and diffuse reflection component analysis, as well as compl ex 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 o f a CCD camera. The full automation of resolving polarization componen ts using liquid crystals not only affords an elegant application, but significantly speeds up the sensing of polarization components and red uces the amount of optical distortion present in the wobbling of a mec hanically rotating polarizer. In our system two twisted nematic liquid crystals are placed in front of a fixed linear polarizer placed in fr ont of a CCD camera. The application of a series of electrical pulses to the liquid crystals in synchronization with the CCD camera video fr ame rate produces a controlled sequence of polarization component imag es that are stored and processed on Datacube boards. We present a sche me for mapping a partial linear polarization state measured at a pixel into hue, saturation and intensity producing a representation for a p artial linear polarization image. Our polarization camera currently se nses partial linear polarization and outputs such a color representati on 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, s pecular reflection and occluding contour segmentations in a fairly com plex scene, and surface orientation constraints.