scholarly journals Simple fish-eye calibration method with accuracy evaluation

Author(s):  
Ciaran Hughes ◽  
Martin Glavin ◽  
Edward Jones
2012 ◽  
Vol 268-270 ◽  
pp. 1553-1557
Author(s):  
Ke Wang ◽  
Liang Liang Wang ◽  
Li Jun Zhao ◽  
Rui Feng Li

In this paper, a calibration method is proposed for fish-eye panoramic camera. We adopt the unifying spherical projection model to represent the optical nature of fisheye camera. Traditional corner detection works unreliably in highly distorted image. Therefore, edge-based corner detection is proposed based on Hough transform. The line segments within corner detection window and their intersection corner points are extracted accurately and reliably due to the robustness of Hough transform. We use the nonlinear optimization technique to estimate the camera parameters. Experimental results demonstrate the performance of our method.


2009 ◽  
Author(s):  
Hideki Komagata ◽  
Ikuo Ishii ◽  
Hideo Makino ◽  
Akira Takahashi ◽  
Daisuke Wakatsuki

Author(s):  
P. Srestasathiern ◽  
N. Soontranon

In this paper, a novel method for the fish-eye lens calibration is presented. The method required only a 2D calibration plane containing straight lines i.e., checker board pattern without a priori knowing the poses of camera with respect to the calibration plane. The image of a line obtained from fish-eye lenses is a conic section. The proposed calibration method uses raw edges, which are pixels of the image line segments, in stead of using curves obtained from fitting conic to image edges. Using raw edges is more flexible and reliable than using conic section because the result from conic fitting can be unstable. The camera model used in this work is radially symmetric model i.e., bivariate non-linear function. However, this approach can use other single view point camera models. The geometric constraint used for calibrating the camera is based on the coincidence between point and line on calibration plane. The performance of the proposed calibration algorithm was assessed using simulated and real data.


Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1218 ◽  
Author(s):  
Kang Choi ◽  
Yongil Kim ◽  
Changjae Kim

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.


2013 ◽  
Vol 846-847 ◽  
pp. 574-577
Author(s):  
Jian Hui Wu ◽  
Guo Yun Zhang ◽  
Long Yuan Guo ◽  
Shuai Yuan

A staring and nothing blind-zone video surveillance system was designed based on the DSP chip of TMS320DM6467 and the fish-eye lens which has ultra-view field. This fisheye lens has 185 degree field of view, and make the system has 360 degree panorama and nothing blind-zone monitoring which used two fish-eye lens imaging system. Firstly, this paper designed the panorama imaging system, and then studied the calibration method for it. The hardware system used the multimedia imagery processing chip of TMS320DM6467 which has dual core processor and can processing the fish-eye image real time. The experiment shows the fisheye image had 360 degree sphere with nothing blind-zone for surveillance area and the hardware of processing center can work stable. This system can intelligent surveillance when upload the algorithm.


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