A new problem of automatically designing an optimal stereo vision system using two omni-directional catadioptric cameras to yield the highest 3D data accuracy is studied. Factors of the system configuration considered in the design include camera pose, FOV, and mirror shape. To find the optimal vision system configuration, an analytic formula is derived to model the 3D measurement error, which takes into consideration the variations of pixel-quantization precisions and angular resolutions in images by conducting error propagation analysis in the data computation process. The formula is then used in an optimization framework to find the optimal system configurations for different shapes of system setup environments. For regular cases with rectangular cuboid-shaped 3D measurement and camera placement areas, two fast algorithms are proposed to solve the problem, one being bisection-based and relatively slower for deriving the optimal solution; and the other faster using analytic formulas for deriving a sub-optimal solution which is proved to be close to the optimal one in precision. Experimental results of simulations and real application cases show the feasibility of the proposed method.Index Terms-stereo vision system, omni-cameras, optimal system configuration, 3D data measurement accuracy. Claim 2. A larger value of D y always yields a smaller value of the criterion function E w .

A stereo vision system using two omni-cameras for 3-D vision applications is proposed, which has an automatic adaptation capability to any system setup before 3-D data computation is conducted. The adaptation, which yields the orientations and distance of the two omni-cameras, is accomplished by detecting and analyzing the horizontal lines appearing in the omni-images acquired with the cameras and a person standing in front of the cameras. Properties of line features in environments are utilized for detecting more precisely the horizontal lines that appear as conic sections in omni-images. The detection work is accomplished through the use of carefully chosen parameters and a refined Hough transform technique. The detected horizontal lines are utilized to compute the cameras' orientations and distance from which the 3-D data of space points are derived analytically. Compared with a traditional system using a pair of projective cameras with nonadjustable camera orientations and distance, the proposed system has the advantages of offering more flexibility in camera setups, better usability in wide areas, higher precision in computed 3-D data, and more convenience for nontechnical users. Good experimental results show the feasibility of the proposed system. Index Terms-3-D vision applications, automatic adaptation, omni-camera, omni-image, stereo vision, system setup.

No abstract

No abstract

No abstract