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Proceedings Paper

Stereoscopic 3D reconstruction using motorized zoom lenses within an embedded system
Author(s): Pengcheng Liu; Andrew Willis; Yunfeng Sui
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Paper Abstract

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.

Paper Details

Date Published: 2 February 2009
PDF: 12 pages
Proc. SPIE 7251, Image Processing: Machine Vision Applications II, 72510W (2 February 2009); doi: 10.1117/12.805732
Show Author Affiliations
Pengcheng Liu, The Univ. of North Carolina at Charlotte (United States)
Andrew Willis, The Univ. of North Carolina at Charlotte (United States)
Yunfeng Sui, The Univ. of North Carolina at Charlotte (United States)


Published in SPIE Proceedings Vol. 7251:
Image Processing: Machine Vision Applications II
Kurt S. Niel; David Fofi, Editor(s)

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