Binocular Stereo Vision System Research Articles

Binocular Stereo Vision System for Measuring Distance of Apples in Orchard (Part 1)

Binocular Stereo Vision System for Measuring Distance of Apples in Orchard (Part 1)

Binocular Stereo Vision System for Measuring Distance of Apples in Orchard (Part 2)

Binocular Stereo Vision System for Measuring Distance of Apples in Orchard (Part 2)

Binocular Stereo Vision System for Measuring Distance of Apples in Orchard (Part 3) Influences of conditions of image input on the error of distance measurement

Binocular Stereo Vision System for Measuring Distance of Apples in Orchard (Part 3) Influences of conditions of image input on the error of distance measurement

Integration of a stereo vision system and a laser range finder for 3-D construction

In this article, we investigate the problem of integrating a binocular stereo vision system and a laser range finder to construct a 3-D map of the environment. The proposed scheme is realized by using the alignment parameters obtained in the 2-D map construction of the laser range finder for the 3-D data generated by the stereo vision system. The 2-D map alignment task is formulated as an optimization problem of minimizing the alignment errors between local maps and selected parts of the developing global map. The problem is then solved using the Simplex method. To increase the robustness of the searching process, multiple initial guesses are provided in the Simplex method. The performance of the proposed architecture is verified by experimental results from a mobile vehicle for obstacle avoidance.

Sound source localization based on audio-video system of mobile robot

For the accuracy of sound source localization,the authors provided an algorithm which estimated the sound azimuth roughly through the auditory system of robot.Based on this evaluation,the survey used binocular stereo vision system to compensate the direction error,and located the elevation degree in vertical plane and the distance of sound source.The experimental results show that the coarse-to-fine strategy has more precise result for sound source localization.

Pseudostereo-Vision System: A Monocular Stereo-Vision System as a Sensor for Real-Time Robot Applications

In this paper, the design and the construction of a new system for stereo vision using planar mirrors and a single camera are presented. Equations giving the coordinates of a point in space are provided. In these equations, refraction phenomena due to the beam splitter used have been taken into consideration. Two virtual cameras are created from this pseudostereo-vision system with exactly the same geometric properties, parameters, and angular field of view of the real camera. Two superimposed stereo images are simultaneously received as a complex image. This vision system has no moving parts, its construction is quite simple, and it is mechanically robust and cheap. It can be used for accurate measurements in the same way as binocular stereo-vision systems. It is easy to mount this system on the end effector of a robotic manipulator or on a mobile robot for real-time applications. Using fast algorithms for point correspondence and depth calculation on a simple personal computer, it can be used in high-speed, low-cost, and high-accuracy applications.

Application of Stereovision to the Mechanical Characterisation of Ceramic Refractories Reinforced with Metallic Fibres

Abstract: Optical methods that yield displacement or strain fields are now emerging significantly in the mechanical sciences. At the Research Center on Tools, Materials and Forming Processes (CROMeP) at École des Mines d'Albi, a binocular stereovision system has been developed that can be used to measure: (a) the three‐dimensional (3D) shape of a static object, or (b) the surface strains of an object undergoing some 3D mechanical or thermal stress. In this paper, the application of the stereovision technique to investigate the behaviour of ceramic refractories reinforced with metallic fibres is presented: (i) after the rupture of the sample for assessing the 3D orientation of the fibres in order to correlate a micro‐mechanical model of fibre pullout with the macro‐mechanical results of tensile tests, and (ii) during a tensile test for measuring the 3D displacement/strain field around a notch.

A Technique for Binocular Stereo Vision System Calibration by the Nonlinear Optimization and Calibration Points with Accurate Coordinates

With the increasing need for higher accuracy measurement in computer vision, the precision of camera calibration is a more important factor. The objective of stereo camera calibration is to estimate the intrinsic and extrinsic parameters of each camera. We presented a high-accurate technique to calibrate binocular stereo vision system having been mounted the locations and attitudes, which was realized by combining nonlinear optimization method with accurate calibration points. The calibration points with accurate coordinates, were formed by an infrared LED moved with three-dimensional coordinate measurement machine, which can ensure indeterminacy of measurement is 1/30000. By using bilinear interpolation square-gray weighted centroid location algorithm, the imaging centers of the calibration points can be accurately determined. The accuracy of the calibration is measured in terms of the accuracy in the reconstructing calibration points through triangulation, the mean distance between reconstructing point and given calibration point is 0.039mm. The technique can satisfy the goals of measurement and camera accurate calibration.

Virtual stereovision system: new understanding on single-lens stereovision using a biprism

Some new understanding of a single-lens binocular stereovision system using a biprism (2F filter) is presented. One image captured by this system is divided into two halves and assumed to be one stereo image pair captured by two virtual cameras generated by the biprism. Hence, this system can also be called a virtual stereovision system. Two different approaches to understanding this system are introduced. One approach is based on a camera calibration technique and another is based on a geometrical analysis of ray sketching. Both approaches enable this system to perform depth recovery in a close range like a typical stereovision system. As the approach based on geometrical analysis requires no complex calibration, great implementation and calibration effort can be saved, in contrast with a normal stereovision system. This approach provides a way to build a binocular stereovision system with a simpler implementation but sufficient accuracy. A complete analysis of this system and the related calibration, depth recovery, and experimentation techniques are presented. Experimentation results are presented to prove the effectiveness of both approaches used to understand this system.

A simple rectification method for linear multi-baseline stereovision system.

The linear multi-baseline stereo system introduced by the CMU-RI group has been proven to be a very effective and robust stereovision system. However, most traditional stereo rectification algorithms are all designed for binocular stereovision system, and so, cannot be applied to a linear multi-baseline system. This paper presents a simple and intuitional method that can simultaneously rectify all the cameras in a linear multi-baseline system. Instead of using the general 8-parameter homography transform, a two-step virtual rotation method is applied for rectification, which results in a more specific transform that has only 3 parameters, and more stability. Experimental results for real stereo images showed the presented method is efficient.

A New Model of Binocular Stereo Coordinate Measurement System Based on Skew Ray Tracing

Two-CCD binocular stereo vision systems using pinhole model are attracting research interest in many important fields such as 3-D coordinate measurement. However, new system modeling is difficult because of lack of fundamental imaging formation theory. In this paper, in order to measure a 3-D surface, we demonstrate how a binocular stereo vision system can be modeled by the proposed skew ray tracing method to study the geometric relations between the binocular camera images and the 3-D surface. In order to investigate the overall accuracy and resolution of this system, the influence of infinitesimal camera reading errors on measured coordinate errors is determined by sensitivity analysis. Experimental verification demonstrates that the performance of the proposed system is excellent.

A BINOCULAR STEREOVISION SYSTEM FOR TRANSPLANT GROWTH VARIABLES ANALYSIS

Plug transplant production technology has been widely used in the plant production industry and is continuing to expand in scale. In order to achieve optimal control of the environment for a population of transplants growing in multi–cell plug trays, frequent measurement of the population.s structural and functional properties is required. A binocular stereovision system incorporating two digital cameras and two computers was developed, based on a pixel stereological algorithm, to analyze the aggregate growth variables of a plug tray of transplants. Three–dimensional (3–D) color images of the transplant population were reconstructed from pairs of digital two–dimensional (2–D) color images taken under a constant light environment. Sweet potato (Ipomoea batatas (L.) Lam.) was used as a test plant. Average height, leaf area, projected leaf area, and mass volume of the transplant population were calculated at a pixel level by extracting four user–selected colors. Image analysis took 2 to 3 min for each transplant population measurement. The aggregate growth variables of the transplant population calculated from image analysis correlated closely with corresponding average height, leaf area, and fresh and dry masses determined from destructive measurements. The binocular stereovision system using the pixel stereological algorithm successfully estimated the values of the transplant growth variables. This image analysis method has the potential to automatically provide necessary aggregate transplant physical properties for identifying growth responses to various environmental conditions. This technique will in turn lead to the selection of optimum environmental conditions for transplant growth.

Improvement of a Binocular Stereovision System by Using Artificial Neural Networks.

Improvement of a Binocular Stereovision System by Using Artificial Neural Networks.

New Stereovision for Human-Robot Communications

Better communications between robots and humans requires an understanding of human senses, and at the same time, the ability to express these senses. Robot functions must be able to approximate as much as possible the five human senses of sight, hearing, smell, taste and touch. Further, the system in which these five senses are integrated must be understood. The expression of such senses by robots should not be confined to merely simulating human behaviors but needs to address unknown and difficult problems related to the manifestation of the inner aspects of human mentality. In this paper, we report on a new artificial vision system that is similar to the human sense of sight, with the target of realizing functions for understanding the processes of human sight. First, we introduce the new artificial visual sensing system and explain problems of virtual images and occlusion, blind spots in conventional binocular stereovision systems. We then discuss a technique for solving these problems that utilizes the new functions of the artificial vision system we developed and introduce a prototype of the new system and its configuration.

Hierarchical Stereo Matching Using Chromatic Information

The key issue in making stereo vision practical is to find a combination of algorithms and hardware that led to reliable, real-time range estimation with a computer system small enough to use on robotic vehicles. In this paper, a matching algorithm to solve the central problem of binocular stereo vision systems is proposed. The algorithm utilizes two primitives of different abstraction undera hierarchical scheme: regions and linear edge segments. The hierarchical scheme greatly improves the efficiency because provides only the needed depth information with the needed degree of resolution. Chromatic information has been used. Color significantly reduces the ambiguity between potential matches and increases the accuracy of the resulting matches.

A 40*40 CCD/CMOS absolute-value-of-difference processor for use in a stereo vision system

An analog VLSI processor chip with application in a high-speed binocular stereo vision system used for the recovery of scene depth is presented. The authors have attempted to exploit the principal advantages of analog VLSI, namely, its small area, high speed, and low power, while minimizing the effects of its limited accuracy, inflexibility, and lack of storage capacity. A CCD/CMOS stereo system implementation, capable of processing several thousand image frame pairs per second for 40*40-pixel binocular images, is proposed. A 40*40-pixel absolute-value-of-difference (AVD) array, a core processor of the stereo system, was fabricated in a 2- mu m CCD/CMOS process. Individual unit cells in the array were characterized and tested. The array functionality was tested by imbedding it in a computerized stereo system and using both real-scene and computer-generated input image pairs. The system output is compared with full computer simulations for the same image pairs, showing good correlation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Dynamic stereo with self-calibration

An approach for incremental refinement of disparity maps obtained from a dynamic stereo sequence of a static scene is presented. The approach has been implemented using a binocular stereo vision system mounted on a mobile robot. A robust least median of squares based algorithm is given for recovering the camera motion between successive viewpoints, which provides a self-calibration mechanism. The recovered motion is utilized for recursive disparity prediction and refinement using a robust Kalman filter model. >