This paper describes a novel embedded system capable of estimating 3D positions of surfaces viewed by a stereoscopic rig
consisting of a pair of calibrated cameras. Novel theoretical and technical aspects of the system are tied to two aspects of
the design that deviate from typical stereoscopic reconstruction systems: (1) incorporation of an 10x zoom lens (Rainbow-
H10x8.5) and (2) implementation of the system on an embedded system. The system components include a DSP running
μClinux, an embedded version of the Linux operating system, and an FPGA. The DSP orchestrates data flow within the
system and performs complex computational tasks and the FPGA provides an interface to the system devices which consist
of a CMOS camera pair and a pair of servo motors which rotate (pan) each camera. Calibration of the camera pair is
accomplished using a collection of stereo images that view a common chess board calibration pattern for a set of pre-defined
zoom positions. Calibration settings for an arbitrary zoom setting are estimated by interpolation of the camera parameters.
A low-computational cost method for dense stereo matching is used to compute depth disparities for the stereo image pairs.
Surface reconstruction is accomplished by classical triangulation of the matched points from the depth disparities. This
article includes our methods and results for the following problems: (1) automatic computation of the focus and exposure
settings for the lens and camera sensor, (2) calibration of the system for various zoom settings and (3) stereo reconstruction
results for several free form objects.