Monocular Stereo Vision Research Articles

Research on Monocular Depth Sensing Method Based on Liquid Zoom Imaging

Monocular stereo vision has excellent application prospects in the field of microrobots. On the basis of the geometric model of bifocal imaging, this paper proposes a monocular depth perception method by liquid zoom imaging. Firstly, the configuration of a monocular liquid vision system for depth measurement is presented, and the working mechanism of the system is analyzed through theoretical derivation. Then, to eliminate the influence of optical axis drift induced by the liquid gravity factor on the measurement results, the target image area is used as the calculation feature instead of the image vector length. A target area calculation method based on chain code classification and strip segmentation is proposed. Furthermore, in response to the fluctuation problem of liquid lens focal power caused by factors such as temperature and object distance, a dynamic focal length model of the liquid zoom imaging system is constructed after precise calibration of the focal power function. Finally, a testing experiment is designed to validate the proposed method. The experimental results show that the average error of depth perception methods is 4.30%, and its measurement time is only on the millisecond scale. Meanwhile, the proposed method has good generalization performance.

Influence Evaluation of Systematic Errors and Prismatic Postures on Field of View in Monocular Stereo Vision

Influence Evaluation of Systematic Errors and Prismatic Postures on Field of View in Monocular Stereo Vision

Light Field Display Based on Monocular Stereo Vision

Light Field Display Based on Monocular Stereo Vision

Target Positioning and Grasping of NAO Robot Based on Monocular Stereo Vision

With the continuous advancement of science and technology and the rapid development of robotics, it has become an inevitable trend for domestic robots to enter thousands of households. In order to solve the inconvenience problem of the elderly and people with special needs, because the elderly and other people in need may need the help of domestic robots due to inconvenient legs and feet, the research of the robot target position based on monocular stereo vision and the understanding of the robot NAO are very important. Research and experiments are carried out on the target recognition and positioning in the process of NAO robot grasping. This paper proposes a recognition algorithm corresponding to quantitative component statistical information. First, extract the area of interest that contains the purpose from the image. After that, to eliminate interference in various fields and achieve target recognition, the robot cameras have almost no common field of view and can only use one camera at the same time. Therefore, this article uses the monocular vision principle to locate the target, and the detection algorithm is based on the structure of the robot head material, establishes the relationship between the height change of the machine head and the tilt angle, and improves the monocular vision NAO robot detection algorithm. According to experiments, the accuracy of the robot at close range can be controlled below 1 cm. This article completes the robot’s grasping and transmission of the target. About 80% of the external information that humans can perceive comes from vision. In addition, there are advantages such as high efficiency and good stability.

Spatial light path analysis and calibration of four-mirror-based monocular stereo vision.

The feasibility and accuracy of four-mirror-based monocular stereo vision (FMSV) are related to the system layout and calibration accuracy, respectively. In this study, a spatial light path analysis method and a calibration method are proposed for an FMSV system. As two-dimensional light path analysis cannot fully characterize the imaging parameters, a spatial light path model is proposed, which allows refinement of the system design. Then, considering the relationship between the lens distortion and the imaging depth of field (DoF), a DoF-distortion equal-partition-based model is established. In the traditional calibration method, the optical axis must be perpendicular to the chessboard. Here, an accurate and practical FMSV calibration method without this constraint is proposed based on the above model. Using the proposed spatial light path analysis technique, a high-accuracy, high-portability FMSV system is constructed and calibrated, for which the average error of the vision-reconstructed distance is 0.0298 mm. In addition, robot path accuracy is evaluated by the system and compared to laser-tracker measurement results. Hence, high accuracy of 0.031 mm is determined for the proposed vision system.

Algorithm for epipolar geometry and correcting monocular stereo vision based on a plane mirror

Based on the epipolar geometry of binocular stereo vision, the epipolar geometry of monocular stereo vision with a plane mirror is studied. This paper analyses the imaging principle of monocular stereo vision with a plane mirror, the epipolar constraint equation for monocular stereo vision is deduced, and the constraint relationship between two image points of an object in an image is discussed. We also discuss the epipolar correction of monocular stereo vision and the results of both simulated and real experiments. The experiment shows that the epipolar correction of monocular stereo vision proposed in this paper is completely correct and feasible, which provides the basis for the follow-up study of monocular stereo vision with a plane mirror.

Biprism-based monocular stereovision system parameter optimization

Biprism-based monocular stereovision systems can acquire different views of the same object at a single shot, which have several advantages over conventional two-camera systems. To measure the position or recover the shape of the object, effective image pairs have to be captured first, which depends on the field of view of the system. In this paper, we propose a common method for establishing a practical biprism-based monocular stereovision system. The relationship between system parameters and object distance has been analyzed in details. The criterion for parameter optimization and procedure for system setup have been introduced. Experimental results show that our method can effectively calculate different conditions under different parameters and optimize the parameter configurations for the particular system.

Research on Cotton Row Detection Algorithm Based on Binocular Vision

As a relative locating method, machine vision is generally used for automatic navigation of cotton cultivator or cotton insecticide sprayer. However, it is difficult to achieve reliable and stable recognition of crop row with monocular stereo vision system, because it neither can access directly to the depth information of the image, which leads to massive time-consuming calculation, nor possess high-accuracy recognition or a good anti-noise property. This paper presents an algorithm for cotton row detection based on binocular stereo vision to be used for automatic navigation of cotton cultivator. The Zhang's plane calibration is used to obtain the internal and external parameters of the binocular stereo vision. Preprocessing means are applied to distinguish the cotton from soil, stereoscopic match is conducted according to the SIFT operators after the preprocessing of images, after which cotton space three-dimensional coordinates are acquired by parallax distance measuring method, with the elevation information combination of Hough transform, cotton lines are finally detected. The detection results indicate that this method has an accuracy higher than 90%, which primarily meets the need of automatic navigation for cotton cultivator.

Study on Stereo Vision for 3D Reconstruction of Welding Seam

The Monocular stereo vision sensor based on structured light is designed and invented for the detection of the weld seam. By incorporating the structured light, the corresponding points matching problem in the stereo vision has been solved effectively. Firstly, the built monocular stereo vision system is used to obtain the image information of seam surface. Then the image coordinate of the seam feature points in the two-dimensional plane can be identified and extracted, through the responding image processing and feature analysis of the seam image collected. After that, the three-dimensional coordinates are calculated by using the theory of projective geometry according to the positional relation between the CCD camera and structured light projected in the seam surface. By this way, the seam feature information such as the three-dimensional geometry sizes, the groove type, the angle, and the interval can be obtained. Finally, the algorithm performance is tested by the experiment of obtaining the three-dimensional coordinate for seams center points, and the results have proved the detection accuracy and reliability of the visual collection system.

Extracting disparity map from bifocal monocular stereo vision in a novel way

Disparity is a key point in stereo vision as it shows the depth information of the scene indirectly,and disparity calculation is the basis of the depth calculation.The traditional disparity calculation methods are all targeted at binocular stereo.However,compared with disparity in binocular,the disparity in monocular stereo is radial along epipolar line.Concerning the characteristics of bi-focal monocular stereo vision,an approach to get disparity map from bi-focal images was proposed in this paper.Preliminary depth map was obtained by matching cost calculated.By using Mean-Shift algorithm,discontinuities and misunderstandings in primary depth map were smoothed and eliminated according to the matched points and graph cut result.The experimental results show that this method can get disparity map efficiently from pairs of bi-focal images.

Modeling and Error Analysis of Monocular Stereo Vision System for Large-Scale Workpiece On-Machine Measurement

A novel movable monocular stereo vision measurement system was designed considering the application objectives and on-machine measurement situation. The physical model and mathematical model for measurement accuracy was established. The appropriate structure parameters scope was obtained after simulation analysis. Finally, an application example of the measurement system is introduced.

ReSSAC UAV EXPLORING, DECIDING AND LANDING IN A PARTIALLY KNOWN ENVIRONMENT

In the ReSSAC project, two uninhabited rotorcraft have been equipped with a dependable supervision architecture implementing autonomous capabilities of reactive obstacle avoidance, navigation, take-off, landing, perception and decision. It can localize surrounding obstacles thanks to an embedded monocular stereovision system. It can adapt to its environment and replan its (motion and perception) action strategy taking into account uncertainties due to atmospheric conditions, or due to the ill-known map of the terrain, potentially obstructed by obstacles. A variety of flight demonstrations of the ReSSAC UAV exploring, deciding and landing in a partially known unprepared non-cooperative environment have been performed.