Refinement of depth from stereo camera ego-motion parameters

Skulimowski, Piotr; Strumiłło, Paweł

doi:10.1049/el:20080441

Cited by 11 publications

(11 citation statements)

References 3 publications

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“…The displacement of the image points determined from (7) on the basis of the values of the angles in (10) was up to 0.1653 pixels on the x-axis and 0.0766 pixels on the y-axis. These values indicate a very low level of the estimation error for the camera rotation angles, allowing accurate determination of disparity from rectified images [10].…”

Section: Experimental Verification Of the Camera Calibration Techniquementioning

confidence: 89%

Automatic Calibration of Stereoscopic Cameras in an Electronic Travel Aid for the Blind

Pawe¹,

Ostrowski²

2013

Metrology and Measurement Systems

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The article describes a technique developed for identification of extrinsic parameters of a stereovision camera system for the purpose of image rectification without the use of reference calibration objects. The goal of the presented algorithm is the determination of the mutual position of cameras, under the assumption that they can be modeled by pinhole cameras, are separated by a fixed distance and are moving through a stationary scene. The developed method was verified experimentally on image sequences of a scene with a known structure.

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Section: Experimental Verification Of the Camera Calibration Techniquementioning

confidence: 89%

Automatic Calibration of Stereoscopic Cameras in an Electronic Travel Aid for the Blind

Pawe¹,

Ostrowski²

2013

Metrology and Measurement Systems

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“…Predicting this movement is important in the case of the intended application in a head-mounted stereovision system, where the main causes of motion in the image are the rotations of the user's head. Estimation of the camera egomotion vector requires a number of image analysis operations:  colour image conversion to greyscale, distortion correction and rectification,  detection of characteristic points -image corners and determination of their motion [3],  estimation of the disparity between the position of these points in the left and right image of stereoscopic pair with the use of a block matching technique [5],  estimation of corner displacements between consecutive images in the sequence. Image characteristic points, in this case corners, are detected with a standard Harris detector.…”

Section: Local Navigation On the Basis Of A Stereoscopic Image Sequencementioning

confidence: 99%

Motion Vector Estimation of a Stereovision Camera with Inertial Sensors

Pełczyński¹,

Ostrowski²,

Rzeszotarski³

2012

Metrology and Measurement Systems

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The aim of the presented work was the development of a tracking algorithm for a stereoscopic camera setup equipped with an additional inertial sensor. The input of the algorithm consists of the image sequence, angular velocity and linear acceleration vectors measured by the inertial sensor. The main assumption of the project was fusion of data streams from both sources to obtain more accurate ego-motion estimation. An electronic module for recording the inertial sensor data was built. Inertial measurements allowed a coarse estimation of the image motion field that has reduced its search range by standard image-based methods. Continuous tracking of the camera motion has been achieved (including moments of image information loss). Results of the presented study are being implemented in a currently developed obstacle avoidance system for visually impaired pedestrians.

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“…A more detailed description of how the processing of the stereovision data is carried out is given in (Skulimowski, 2007(Skulimowski, & 2008. …”

Section: D Scene Sonification Conceptmentioning

confidence: 99%