Polarization camera for computer vision with a beam splitter

A fully automated system that utilizes two CCD cameras and a polarizing beam splitter to create a polarization camera capable of sensing the polarization of reflected light from objects at pixel resolution is presented. The physical dimensions of the polarization of light beyond that of intensity carry extra information from a scene that can provide a richer set of descriptive physical constraints for the understanding of images. It has been shown that polarization cues can be used to perform dielectric and metal material identification and specular-and diffuse-reflection component analysis, as well as complex image segmentations that would be immensely more complicated or even infeasible with the use of intensity and color alone. A polarizing-plate beam splitter is placed in front of two CCD cameras so that light beams reflected from and transmitted through the beam splitter are each incident upon a separate camera. The polarization state of the reflected and the transmitted beams are linearly independent in terms of two orthogonal-polarization components, and these components are resolved in real time from the simple solution of two simultaneous linear equations. The polarizing-plate beam splitter allows for the simultaneous measurement of two orthogonal-polarization components over fairly wide field views suitable for vision and robotics. A polarization contrast image can be produced at 15 Hz. Two sets of orthogonal-polarization component pairs can be resolved by electronically switching a twisted nematic liquid crystal placed in front of the beam splitter, permitting the real-time measurement of partial-linear-polarization images at 7.5 Hz. A scheme for mapping states of partial linear polarization into hue, saturation, and intensity, which is a very suitable representation for a polarization image, is illustrated. The unique vision-understanding capabilities of this polarization camera system are demonstrated with experimental results showing polarization-based dielectric and metal material classification, shape constraints from reflected polarization, and specular-reflection and occluding-contour segmentations in a fairly complex scene.