The Experts below are selected from a list of 63726 Experts worldwide ranked by ideXlab platform

Olli Silven - One of the best experts on this subject based on the ideXlab platform.

  • Four-step camera Calibration Procedure with implicit image correction
    Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1997
    Co-Authors: Janne Heikkilä, Olli Silven
    Abstract:

    In geometrical camera Calibration the objective is to determine a\nset of camera parameters that describe the mapping between 3-D reference\ncoordinates and 2-D image coordinates. Various methods for camera\nCalibration can be found from the literature. However surprisingly\nlittle attention has been paid to the whole Calibration Procedure, i.e.,\ncontrol point extraction from images, model fitting, image correction,\nand errors originating in these stages. The main interest has been in\nmodel fitting, although the other stages are also important. In this\npaper we present a four-step Calibration Procedure that is an extension\nto the two-step method. There is an additional step to compensate for\ndistortion caused by circular features, and a step for correcting the\ndistorted image coordinates. The image correction is performed with an\nempirical inverse model that accurately compensates for radial and\ntangential distortions. Finally, a linear method for solving the\nparameters of the inverse model is presented

  • Calibration Procedure for short focal length off the shelf ccd cameras
    International Conference on Pattern Recognition, 1996
    Co-Authors: Janne Heikkilä, Olli Silven
    Abstract:

    A camera Calibration Procedure intended for a 3D measurement application is presented, paying attention to the various error sources. The error may be measurement noise that is random by nature, but it may also be systematic originating from the Calibration target used, geometrical distortions and illumination. In order to obtain good Calibration results, the systematic error sources should be eliminated or their effects compensated for. Then, the camera parameters can be determined by fitting the corrected measurements to the camera model which in our case is a combination of a pinhole camera and lens distortion models. We also notice that a more complete camera model is needed to explain all the error components.

  • CVPR - A four-step camera Calibration Procedure with implicit image correction
    Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1
    Co-Authors: Janne Heikkilä, Olli Silven
    Abstract:

    In geometrical camera Calibration the objective is to determine a set of camera parameters that describe the mapping between 3-D reference coordinates and 2-D image coordinates. Various methods for camera Calibration can be found from the literature. However surprisingly little attention has been paid to the whole Calibration Procedure, i.e., control point extraction from images, model fitting, image correction, and errors originating in these stages. The main interest has been in model fitting, although the other stages are also important. In this paper we present a four-step Calibration Procedure that is an extension to the two-step method. There is an additional step to compensate for distortion caused by circular features, and a step for correcting the distorted image coordinates. The image correction is performed with an empirical inverse model that accurately compensates for radial and tangential distortions. Finally, a linear method for solving the parameters of the inverse model is presented.

Janne Heikkilä - One of the best experts on this subject based on the ideXlab platform.

  • Four-step camera Calibration Procedure with implicit image correction
    Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1997
    Co-Authors: Janne Heikkilä, Olli Silven
    Abstract:

    In geometrical camera Calibration the objective is to determine a\nset of camera parameters that describe the mapping between 3-D reference\ncoordinates and 2-D image coordinates. Various methods for camera\nCalibration can be found from the literature. However surprisingly\nlittle attention has been paid to the whole Calibration Procedure, i.e.,\ncontrol point extraction from images, model fitting, image correction,\nand errors originating in these stages. The main interest has been in\nmodel fitting, although the other stages are also important. In this\npaper we present a four-step Calibration Procedure that is an extension\nto the two-step method. There is an additional step to compensate for\ndistortion caused by circular features, and a step for correcting the\ndistorted image coordinates. The image correction is performed with an\nempirical inverse model that accurately compensates for radial and\ntangential distortions. Finally, a linear method for solving the\nparameters of the inverse model is presented

  • Calibration Procedure for short focal length off the shelf ccd cameras
    International Conference on Pattern Recognition, 1996
    Co-Authors: Janne Heikkilä, Olli Silven
    Abstract:

    A camera Calibration Procedure intended for a 3D measurement application is presented, paying attention to the various error sources. The error may be measurement noise that is random by nature, but it may also be systematic originating from the Calibration target used, geometrical distortions and illumination. In order to obtain good Calibration results, the systematic error sources should be eliminated or their effects compensated for. Then, the camera parameters can be determined by fitting the corrected measurements to the camera model which in our case is a combination of a pinhole camera and lens distortion models. We also notice that a more complete camera model is needed to explain all the error components.

  • CVPR - A four-step camera Calibration Procedure with implicit image correction
    Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1
    Co-Authors: Janne Heikkilä, Olli Silven
    Abstract:

    In geometrical camera Calibration the objective is to determine a set of camera parameters that describe the mapping between 3-D reference coordinates and 2-D image coordinates. Various methods for camera Calibration can be found from the literature. However surprisingly little attention has been paid to the whole Calibration Procedure, i.e., control point extraction from images, model fitting, image correction, and errors originating in these stages. The main interest has been in model fitting, although the other stages are also important. In this paper we present a four-step Calibration Procedure that is an extension to the two-step method. There is an additional step to compensate for distortion caused by circular features, and a step for correcting the distorted image coordinates. The image correction is performed with an empirical inverse model that accurately compensates for radial and tangential distortions. Finally, a linear method for solving the parameters of the inverse model is presented.

Giulio Barbato - One of the best experts on this subject based on the ideXlab platform.

  • Calibration Procedure for a laser triangulation scanner with uncertainty evaluation
    Optics and Lasers in Engineering, 2016
    Co-Authors: Gianfranco Genta, Paolo Minetola, Giulio Barbato
    Abstract:

    Abstract Most of low cost 3D scanning devices that are nowadays available on the market are sold without a user Calibration Procedure to correct measurement errors related to changes in environmental conditions. In addition, there is no specific international standard defining a Procedure to check the performance of a 3D scanner along time. This paper aims at detailing a thorough methodology to calibrate a 3D scanner and assess its measurement uncertainty. The proposed Procedure is based on the use of a reference ball plate and applied to a triangulation laser scanner. Experimental results show that the metrological performance of the instrument can be greatly improved by the application of the Calibration Procedure that corrects systematic errors and reduces the device's measurement uncertainty.

Matteo Panciroli - One of the best experts on this subject based on the ideXlab platform.

  • Intelligent Vehicles Symposium - A lasers and cameras Calibration Procedure for VIAC multi-sensorized vehicles
    2012 IEEE Intelligent Vehicles Symposium, 2012
    Co-Authors: Luca Mazzei, Paolo Medici, Matteo Panciroli
    Abstract:

    This paper proposes an efficient Calibration Procedure designed for the vehicle prototypes involved in the VisLab Intercontinental Autonomous Challenge [1]. The perception system is based on laser rangefinders and cameras, for their complementary purpose. An high precision pose estimation must be carried out by a very precise Calibration Procedure, in order to convert information between different coordinate systems. A modular approach has been extensively tested during VIAC which has offered a unique chance to face pros and cons of different Calibration Procedures; data collected during the expedition has also become a reference benchmark for further improvements.

T.j. Pack - One of the best experts on this subject based on the ideXlab platform.

  • ICRA - Calibration Procedure for an industrial robot
    Proceedings. 1988 IEEE International Conference on Robotics and Automation, 1
    Co-Authors: B. Mooring, T.j. Pack
    Abstract:

    A Calibration Procedure for a manipulator in a typical industrial environment is investigated. The Calibration problem is posed, and the constraints are listed for the particular task to be addressed. The robot geometry is investigated to locate the primary sources of inaccuracy. A Calibration Procedure is proposed that combines design modifications in the robot with active Calibration fixtures in the workspace. Results of several tests are tabulated to demonstrate the success of the Calibration Procedure. >