Trinocular Stereo Research Articles

A 3D World Model Builder with a Mobile Robot

This article describes a system to incrementally build a world model with a mobile robot in an unknown environment. The model is, for the moment, segment based. A trinocular stereo system is used to build a local map about the environment. A global map is obtained by integrating a sequence of stereo frames taken when the robot navigates in the environment. The emphasis of this article is on the representation of the uncer tainty of 3D segments from stereo and on the integration of segments from multiple views. The proposed representation is simple and very convenient to characterize the uncertainty of segment. A Kalman filter is used to merge matched line seg ments. An important characteristic of our integration strategy is that a segment observed by the stereo system corresponds only to one part of the segment in space, so the union of the different observations gives a better estimate on the segment in space. We have succeeded in integrating 35 stereo frames taken in our robot room.

A cost-benefit analysis of a third camera for stereo correspondence

This paper looks at the twin issues of the gain in accuracy of stereo correspondence and the accompanying increase in computational cost due to the use of a third camera for stereo analysis. Trinocular stereo algorithms differ from binocular algorithms essentially in the epipolar constraint used in the local matching stage. The current literature does not provide any insight into the relative merits of binocular and trinocular stereo matching with the matching accuracy being verified aginst the ground truth. Experiments for evaluating the relative performance of binocular and trinocular stereo algorithms were conducted. The stereo images used for the performance evaluation were generated by applying a Lambertian reflectance model to real Digital Elevation Maps (DEMs) available from the U.S. Geological Survey. The matching accuracy of the stereo algorithms was evaluated by comparing the observed stereo disparity against the ground truth derived from the DEMs. It was observed that trinocular local matching reduced the percentage of mismatches having large disparity errors by more than half when compared to binocular matching. On the other hand, trinocular stereopsis increased the computational cost of local matching over binocular by only about one-fourth. We also present a quantization-error analysis of the depth reconstruction process for the nonparallel stereo-imaging geometry used in our experiments.

Determining motion from 3D line segment matches: a comparative study

Motion estimation is a very important problem in dynamic scene analysis. Although it is easier to estimate motion parameters from 3D data than from 2D images, it is not trivial, since the 3D data we have are almost always corrupted by noise. A comparative study on motion estimation from 3D line segments is presented. Two representations of line segments and two representations of rotation are described. With different representations of line segments and rotation a number of methods for motion estimation are presented, including the extended Kalman filter a general minimization process and the singular value decomposition. These methods are compared using both synthetic and real data obtained by a trinocular stereo. It is observed that the extended Kalman filter with the rotation axis representation of rotation is preferable. Note that all methods discussed can be directly applied to 3D point data.

Trinocular stereo vision for robotics

An approach to building a three-dimensional description of the environment of a robot using three cameras is presented. The main advantages of trinocular versus binocular stereo are simplicity, reliability, and accuracy. It is believed that these advantages make trinocular stereo vision of practical use for many robotics applications. The technique has been successfully applied to several indoor and industrial scenes. Experimental results are presented and discussed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

A new passive measurementmethod by trinocular stereo vision

In the present paper, a new trinocular stereo vision method is proposed. After abrief survey of binocular stereo vision methods, some essential limitations are indicated. A quantitative description of the false target problem in stereo vision is proposed and applied to binocular and trinocular stereo vision. It is shown that a new trinocular stereo vision strategy matching the feature primitives in 3-D space can effectively solve the false targets. The new method for matching trinocular images is then presented. A new calibration method is also proposed and we show that all linear cameras can be transformed into an equilvalent orthonormal one and both the intrinsic and extrinsic parameters of a trinocular stereo vision system can be calibrated without using any 3-D coordinates, which provides a passive measurement system with an auto-calibration capability. A system based on the proposed methods has been realized and tested for computer-generated and real images. The experimental results are satisfactory. Erroneous matching is always less than 1% and the precision for 3-D reconstruction is 2 mm at a distance of about 1.5 m.