Radial Distortion Correction of Fish-Eye Lens Using Straight Lines

2013 ◽  
Vol 432 ◽  
pp. 364-367
Author(s):  
Jong Eun Ha
Keyword(s):  
Distortion Correction ◽  
Eye Lens ◽  
Wide Field ◽  
Lens Model ◽  
Radial Distortion ◽  
Straight Line ◽  
Wide Field Of View ◽  
Planar Pattern ◽  
Straight Lines ◽  
Fish Eye

Fish-eye lens is used in various applications because it can give wide field of view. But, it deviates from the conventional pin-hole camera assumption. It has large radial distortion compared to the conventional lens. In this paper, we present an algorithm for radial distortion correction of fish-eye lens using the property of straight line. First, we estimate the center of radial distortion using the algorithm of Hartely and Kang [4]. We adopt fish-eye lens model of Devernay and Faugeras [5] and estimate the parameter thorough searching. We use planar pattern with chessboard and generate undistorted points by given parameter value. We evaluate the correctness of the parameter by checking the distance of a point to the fitted line. In experiments, we compare proposed algorithm with Wang et al. [6]. Proposed algorithm gives more stable result with less distortion error.

scholarly journals Proposed New AV-Type Test-Bed for Accurate and Reliable Fish-Eye Lens Camera Self-Calibration

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2776
Author(s):  
Kang Hyeok Choi ◽  
Changjae Kim
Keyword(s):  
Outer Part ◽  
Calibration Procedure ◽  
Geometric Distortion ◽  
Eye Lens ◽  
Wide Field ◽  
Test Bed ◽  
Self Calibration ◽  
Type Test ◽  
Balanced Distribution ◽  
Fish Eye

The fish-eye lens camera has a wide field of view that makes it effective for various applications and sensor systems. However, it incurs strong geometric distortion in the image due to compressive recording of the outer part of the image. Such distortion must be interpreted accurately through a self-calibration procedure. This paper proposes a new type of test-bed (the AV-type test-bed) that can effect a balanced distribution of image points and a low level of correlation between orientation parameters. The effectiveness of the proposed test-bed in the process of camera self-calibration was verified through the analysis of experimental results from both a simulation and real datasets. In the simulation experiments, the self-calibration procedures were performed using the proposed test-bed, four different projection models, and five different datasets. For all of the cases, the Root Mean Square residuals (RMS-residuals) of the experiments were lower than one-half pixel. The real experiments, meanwhile, were carried out using two different cameras and five different datasets. These results showed high levels of calibration accuracy (i.e., lower than the minimum value of RMS-residuals: 0.39 pixels). Based on the above analyses, we were able to verify the effectiveness of the proposed AV-type test-bed in the process of camera self-calibration.

scholarly journals A GENERALIZED NON-LINEAR METHOD FOR DISTORTION CORRECTION AND TOP-DOWN VIEW CONVERSION OF FISH EYE IMAGES

2017 ◽  
Vol 36 (2) ◽  
pp. 143 ◽  
Author(s):  
Vivek Singh Bawa ◽  
Krishan Kumar ◽  
Vinay Kumar
Keyword(s):  
Road Traffic ◽  
Linear Method ◽  
Distortion Correction ◽  
Eye Lens ◽  
Computationally Efficient ◽  
Driver Assistance Systems ◽  
Top Down ◽  
Driving Experience ◽  
Generalized Framework ◽  
Fish Eye

Advanced driver assistance systems (ADAS) have been developed to automate and modify vehicles for safety and better driving experience. Among all computer vision modules in ADAS, 360-degree surround view generation of immediate surroundings of the vehicle is very important, due to application in on-road traffic assistance, parking assistance etc. This paper presents a novel algorithm for fast and computationally efficient transformation of input fisheye images into required top down view. This paper also presents a generalized framework for generating top down view of images captured by cameras with fish-eye lenses mounted on vehicles, irrespective of pitch or tilt angle. The proposed approach comprises of two major steps, viz. correcting the fish-eye lens images to rectilinear images, and generating top-view perspective of the corrected images. The images captured by the fish-eye lens possess barrel distortion, for which a nonlinear and non-iterative method is used. Thereafter, homography is used to obtain top-down view of corrected images. This paper also targets to develop surroundings of the vehicle for wider distortion less field of view and camera perspective independent top down view, with minimum computation cost which is essential due to limited computation power on vehicles.

scholarly journals High-Dynamic-Range Imaging for Cloud Segmentation

2017 ◽  
Author(s):  
Soumyabrata Dev ◽  
Florian M. Savoy ◽  
Yee Hui Lee ◽  
Stefan Winkler
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Wide Field ◽  
Single Shot ◽  
Generation Process ◽  
Large Dynamic Range ◽  
Exposure Fusion ◽  
Wide Field Of View ◽  
High Dynamic ◽  
Fish Eye

Abstract. Sky/cloud images obtained from ground-based sky-cameras are usually captured using a fish-eye lens with a wide field of view. However, the sky exhibits a large dynamic range in terms of luminance, more than a conventional camera can capture. It is thus difficult to capture the details of an entire scene with a regular camera in a single shot. In most cases, the circumsolar region is over-exposed, and the regions near the horizon are under-exposed. This renders cloud segmentation for such images difficult. In this paper, we propose HDRSeg – an effective method for cloud segmentation using High-Dynamic-Range (HDR) imaging based on multi-exposure fusion. We describe the HDR generation process and release a new database to the community for benchmarking. Our proposed approach is the first using HDR images for cloud segmentation and achieves very good results.

scholarly journals A Master-Slave Surveillance System to Acquire Panoramic and Multiscale Videos

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Yu Liu ◽  
Shiming Lai ◽  
Chenglin Zuo ◽  
Hao Shi ◽  
Maojun Zhang
Keyword(s):  
Surveillance System ◽  
High Mobility ◽  
Correction Method ◽  
Visual Surveillance ◽  
Distortion Correction ◽  
Wide Field ◽  
Large Area ◽  
Wide Field Of View ◽  
Spatial Calibration ◽  
Realistic Scenes

This paper describes a master-slave visual surveillance system that uses stationary-dynamic camera assemblies to achieve wide field of view and selective focus of interest. In this system, the fish-eye panoramic camera is capable of monitoring a large area, and the PTZ dome camera has high mobility and zoom ability. In order to achieve the precise interaction, preprocessing spatial calibration between these two cameras is required. This paper introduces a novel calibration approach to automatically calculate a transformation matrix model between two coordinate systems by matching feature points. In addition, a distortion correction method based on Midpoint Circle Algorithm is proposed to handle obvious horizontal distortion in the captured panoramic image. Experimental results using realistic scenes have demonstrated the efficiency and applicability of the system with real-time surveillance.

Real-time distortion correction of fish-eye lens based on Bayer image signal

2014 ◽  
Vol 21 (2) ◽  
pp. 162-173 ◽  
Author(s):  
Shiming Lai ◽  
Zhihui Xiong ◽  
Lidong Chen ◽  
Xin Tan ◽  
Maojun Zhang
Keyword(s):  
Real Time ◽  
Distortion Correction ◽  
Eye Lens ◽  
Time Distortion ◽  
Fish Eye

scholarly journals Analysis of Fish-Eye Lens Camera Self-Calibration

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1218 ◽  
Author(s):  
Kang Choi ◽  
Yongil Kim ◽  
Changjae Kim
Keyword(s):  
Test Object ◽  
Focal Length ◽  
Calibration Method ◽  
The Other ◽  
Eye Lens ◽  
Wide Field ◽  
Self Calibration ◽  
Type Test ◽  
Fish Eye ◽  
Test Objects

The fish-eye lens camera offers the advantage of efficient acquisition of image data through a wide field of view. However, unlike the popular perspective projection camera, a strong distortion effect appears as the periphery of the image is compressed. Such characteristics must be precisely analyzed through camera self-calibration. In this study, we carried out a fish-eye lens camera self-calibration while considering different types of test objects and projection models. Self-calibration was performed using the V-, A-, Plane-, and Room-type test objects. In the fish-eye lens camera, the V-type test object was the most advantageous for ensuring the accuracy of the principal point coordinates and focal length, because the correlations between parameters were relatively low. On the other hand, the other test objects were advantageous for ensuring the accuracy of distortion parameters because of the well-distributed image points. Based on the above analysis, we proposed, an accurate fish-eye lens camera self-calibration method that applies the V-type test object. The RMS-residuals of the proposed method were less than 1 pixel.

scholarly journals Human 3D Pose Estimation with a Tilting Camera for Social Mobile Robot Interaction

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4943 ◽  
Author(s):  
Mercedes Garcia-Salguero ◽  
Javier Gonzalez-Jimenez ◽  
Francisco-Angel Moreno
Keyword(s):  
Mobile Robotics ◽  
Real Data ◽  
Human Robot Interaction ◽  
Wide Field ◽  
Fast Method ◽  
Light Conditions ◽  
Robot Interaction ◽  
3D Pose Estimation ◽  
Wide Field Of View ◽  
Fish Eye

Human–Robot interaction represents a cornerstone of mobile robotics, especially within the field of social robots. In this context, user localization becomes of crucial importance for the interaction. This work investigates the capabilities of wide field-of-view RGB cameras to estimate the 3D position and orientation (i.e., the pose) of a user in the environment. For that, we employ a social robot endowed with a fish-eye camera hosted in a tilting head and develop two complementary approaches: (1) a fast method relying on a single image that estimates the user pose from the detection of their feet and does not require either the robot or the user to remain static during the reconstruction; and (2) a method that takes some views of the scene while the camera is being tilted and does not need the feet to be visible. Due to the particular setup of the tilting camera, special equations for 3D reconstruction have been developed. In both approaches, a CNN-based skeleton detector (OpenPose) is employed to identify humans within the image. A set of experiments with real data validate our two proposed methods, yielding similar results than commercial RGB-D cameras while surpassing them in terms of coverage of the scene (wider FoV and longer range) and robustness to light conditions.

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