Efficient and robust extrinsic camera calibration procedure for Lane Departure Warning

Hold, Stephanie; Nunn, Christian; Kummert, Anton; Müller-Schneiders, Stefan

doi:10.1109/ivs.2009.5164308

Cited by 24 publications

(12 citation statements)

References 19 publications

(17 reference statements)

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“…They denote the image coordinates. b is the actual distance between the two camera, f is the camera focus, x L -x R is parallax error, L is the distance between target point P and the camera, namely depth value, according to the basic principle of binocular stereo vision measurement [1]…”

Section: A Binocular Measurement Principlementioning

confidence: 99%

Measurement of Safe Driving Distance Based on Stereo Vision

Hou

Xue

Geng

et al. 2011

2011 Sixth International Conference on Image and Graphics

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The measurement of safe driving distance based on stereo vision is proposed. The model of camera imaging is established using traditional camera calibration method firstly. Secondly, the projection matrix is deduced according to camera's internal and external parameter and used to calibrate the camera. The method of camera calibration based on two-dimensional target plane is adopted. Then the distortion parameters are calculated when the nonlinear geometric model of camera imaging is built. Moreover, the camera's internal and external parameters are optimized on the basis of the projection error' least squares criterion so that the un-distortion image can be obtained. The matching is done between the left image and the right image corresponding to angular point. The parallax error and the distance between the target vehicle and the camera can be calculated. The experimental results show that the measurement scheme is an effective one in a security vehicles spacing survey. The proposed system is convenient for driver to control in time and precisely. It is able to increase the security in intelligent transportation vehicles.

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Section: A Binocular Measurement Principlementioning

confidence: 99%

Measurement of Safe Driving Distance Based on Stereo Vision

Hou

Xue

Geng

et al. 2011

2011 Sixth International Conference on Image and Graphics

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“…For a driving vehicle in an unknown environment, the conventional pointbased method is not possible. Our approach uses relative information, measured distances d ij between points p C,i and p C,j along the x V -axis in driving direction, instead of their absolute coordinates [16]. Therefore, a measurement function ∆g is defined as the Euclidean distance between two points p C,i and p C,j in the V-COS.…”

Section: B Problem Formulationmentioning

confidence: 99%

A novel approach for the online initial calibration of extrinsic parameters for a car-mounted camera

Hold

Gormer

Kummert

et al. 2009

2009 12th International IEEE Conference on Intelligent Transportation Systems

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This paper presents a novel approach for an online initial camera calibration to estimate the extrinsic parameters for vision-based intelligent driver assistance systems. The method uses the periodicity of dashed lane markings and velocity information to determine the extrinsic camera parameters: height, pitch and roll angle. A lane marking detector is utilized to convert the images of road scenes into a set of onedimensional time series. Thereby, the lane marking detector samples the markings at predefined vertical coordinates in the image, so-called scanlines. Based on a correlation analysis and velocity information, the spatial shift between the scanlines is determined. Thus, the distances along the longitudinal lane markings are measured in the coordinate system of the vehicle independently of camera mounting parameters. The GaussNewton algorithm is implemented to minimize the squared error between these estimated distances and the distances obtained by the backprojection to a ground plane using the parameter dependent pinhole camera model. Finally, the approach is evaluated using synthetic and real data with promising results.

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“…Carnegie Mellon University developed a Navlab.X [3] series product system that is based on road flat assumption and using the characteristics of the parallel to the road, such as the lane line, rut, road boundary. University of Parma's PROMETHEUS project has an important part of the GOLD (Generic Obstacle and Lane Detection) [4]. The basic principle of the visual system is using camera as a navigation tool, to analysis the captured image, to detection and extraction of the lanes to avoid obstacles using stereo vision.…”

Section: Introductionmentioning

confidence: 99%

Road marking abrasion defects detection based on video image processing

2016

ISSPJ

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Pavement marking occupies an important position in the road traffic safety operation. A large number of domestic and foreign research and practice has proved that the effective use and maintenance of road signs and markings reduce traffic accidents and improve the capacity of great significance. The main content of this paper is the design of mobile video image acquisition device to road damage to the road traffic marking defect detection, video image to carry out research on road marking based on wear and breakage from video images. The process is random image acquisition of pavement markings, respectively the image pre-processing, image binarization, marking angle correction, marking extraction and detection. Finally, developing software on marking the wear and damage degree detection based on Matlab software then have an image processing experiments. The results show that the software can accurately detect the road wear and damage situation.

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Efficient and robust extrinsic camera calibration procedure for Lane Departure Warning

Cited by 24 publications

References 19 publications

Measurement of Safe Driving Distance Based on Stereo Vision

Measurement of Safe Driving Distance Based on Stereo Vision

A novel approach for the online initial calibration of extrinsic parameters for a car-mounted camera

Road marking abrasion defects detection based on video image processing

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