A Flexible Fringe Projection Vision System with Extended Mathematical Model for Accurate Three-Dimensional Measurement

In order to acquire an accurate three-dimensional (3D) measurement, the traditional fringe projection technique applies complex and laborious procedures to compensate for the errors that exist in the vision system. However, the error sources in the vision system are very complex, such as lens distortion, lens defocus, and fringe pattern nonsinusoidality. Some errors cannot even be explained or rendered with clear expressions and are difficult to compensate directly as a result. In this paper, an approach is proposed that avoids the complex and laborious compensation procedure for error sources but still promises accurate 3D measurement. It is realized by the mathematical model extension technique. The parameters of the extended mathematical model for the ’phase to 3D coordinates transformation’ are derived using the least-squares parameter estimation algorithm. In addition, a phase-coding method based on a frequency analysis is proposed for the absolute phase map retrieval to spatially isolated objects. The results demonstrate the validity and the accuracy of the proposed flexible fringe projection vision system on spatially continuous and discontinuous objects for 3D measurement

A Flexible Fringe Projection Vision System with Extended Mathematical Model for Accurate Three-Dimensional Measurement

In order to acquire an accurate three-dimensional (3D) measurement, the traditional fringe projection technique applies complex and laborious procedures to compensate for the errors that exist in the vision system. However, the error sources in the vision system are very complex, such as lens distortion, lens defocus, and fringe pattern nonsinusoidality. Some errors cannot even be explained or rendered with clear expressions and are difficult to compensate directly as a result. In this paper, an approach is proposed that avoids the complex and laborious compensation procedure for error sources but still promises accurate 3D measurement. It is realized by the mathematical model extension technique. The parameters of the extended mathematical model for the ’phase to 3D coordinates transformation’ are derived using the least-squares parameter estimation algorithm. In addition, a phase-coding method based on a frequency analysis is proposed for the absolute phase map retrieval to spatially isolated objects. The results demonstrate the validity and the accuracy of the proposed flexible fringe projection vision system on spatially continuous and discontinuous objects for 3D measurement

Visual-Inertial first responder localisation in large-scale indoor training environments.

Accurately and reliably determining the position and heading of first responders undertaking training exercises can provide valuable insights into their situational awareness and give a larger context to the decisions made. Measuring first responder movement, however, requires an accurate and portable localisation system. Training exercises of- ten take place in large-scale indoor environments with limited power infrastructure to support localisation. Indoor positioning technologies that use radio or sound waves for localisation require an extensive network of transmitters or receivers to be installed within the environment to ensure reliable coverage. These technologies also need power sources to operate, making their use impractical for this application. Inertial sensors are infrastructure independent, low cost, and low power positioning devices which are attached to the person or object being tracked, but their localisation accuracy deteriorates over long-term tracking due to intrinsic biases and sensor noise. This thesis investigates how inertial sensor tracking can be improved by providing correction from a visual sensor that uses passive infrastructure (fiducial markers) to calculate accurate position and heading values. Even though using a visual sensor increase the accuracy of the localisation system, combining them with inertial sensors is not trivial, especially when mounted on different parts of the human body and going through different motion dynamics. Additionally, visual sensors have higher energy consumption, requiring more batteries to be carried by the first responder. This thesis presents a novel sensor fusion approach by loosely coupling visual and inertial sensors to create a positioning system that accurately localises walking humans in largescale indoor environments. Experimental evaluation of the devised localisation system indicates sub-metre accuracy for a 250m long indoor trajectory. The thesis also proposes two methods to improve the energy efficiency of the localisation system. The first is a distance-based error correction approach which uses distance estimation from the foot-mounted inertial sensor to reduce the number of corrections required from the visual sensor. Results indicate a 70% decrease in energy consumption while maintaining submetre localisation accuracy. The second method is a motion type adaptive error correction approach, which uses the human walking motion type (forward, backward, or sideways) as an input to further optimise the energy efficiency of the localisation system by modulating the operation of the visual sensor. Results of this approach indicate a 25% reduction in the number of corrections required to keep submetre localisation accuracy. Overall, this thesis advances the state of the art by providing a sensor fusion solution for long-term submetre accurate localisation and methods to reduce the energy consumption, making it more practical for use in first responder training exercises

Determining uncertainty in the functional quantities of fringe projection

Fringe projection systems can acquire a point-cloud of more than a million points in minutes while not needing to ever physically touch the measurement surface and can be assembled using relatively inexpensive off-the-shelf components. Fringe projection system can conduct measurements faster than their tactile counterparts and typically require less training to do so. The disadvantage of using a fringe projection system is the measurements are less accurate than alternative tactile methods – and typical methods to obtain an uncertainty evaluation within fringe projection require a tactile system as a comparator. Anterior to any measurement, fringe projection systems undergo a calibration, whereby the set of functional quantities (defined in this thesis as the system parameters) are found that define the measurement (the point-cloud) from the indication (a set of images). The accuracy of the estimated parameters will define the accuracy of any measurements made by the system. The calibration process does not evaluate any uncertainty of the estimated system parameters – the accuracy of the estimation of the parameters remains unknown, as is their exact effect on the measurement result. In this thesis, an investigation into the using the system parameters to evaluate the uncertainty of fringe projection measurements is made. Firstly, a method to localise the centre of ellipses in camera images with an uncertainty is given. This uncertainty is used to derive the uncertainty in the estimated system parameters. The uncertainty in the system parameters is tested by using the system parameters to measure known artefacts, a flatness artefact and two sphere-based artefacts, where the propagated uncertainty is tested against the measurement error. The accuracy of the system parameters are tested by comparing the measurement error of the measurements with measurements made on a commercial system, the GOM ATOS Core 300. In addition, an exhaustive study is undertaken on the calibration, including applying curvature, specificity and parameter stability tests on the non-linear regression used within calibration. The sphere-based measurements were found to not be robust enough against measurement noise in fringe projection to be able to provide information on errors caused by the system parameters. This thesis raises questions as to the appropriateness of using sphere-based measurements to represent the performance of a fringe projection system. The flatness measurements made using the estimated system parameters achieved an accuracy of approximately 30 "μm" across a 300 "mm"×140 "mm" flatness artefact, which is similar to measurements made by the commercial system. However, the estimated uncertainty was unable to explain all measurement discrepancy between the fringe projection measurements and the tactile measurements. The result specificity test indicated poor specificity of the mathematical model of fringe projection, namely the camera pinhole model with Brown-Conrady distortion. It is concluded that the level of accuracy of the mathematical model has become a limiting factor in the accuracy of fringe projection measurements, instead of the accuracy of the inputs to the calibration. Therefore, the uncertainty of the system parameters cannot be used to evaluate an uncertainty of a measurement made using a fringe projection system

Determining uncertainty in the functional quantities of fringe projection

Fringe projection systems can acquire a point-cloud of more than a million points in minutes while not needing to ever physically touch the measurement surface and can be assembled using relatively inexpensive off-the-shelf components. Fringe projection system can conduct measurements faster than their tactile counterparts and typically require less training to do so. The disadvantage of using a fringe projection system is the measurements are less accurate than alternative tactile methods – and typical methods to obtain an uncertainty evaluation within fringe projection require a tactile system as a comparator. Anterior to any measurement, fringe projection systems undergo a calibration, whereby the set of functional quantities (defined in this thesis as the system parameters) are found that define the measurement (the point-cloud) from the indication (a set of images). The accuracy of the estimated parameters will define the accuracy of any measurements made by the system. The calibration process does not evaluate any uncertainty of the estimated system parameters – the accuracy of the estimation of the parameters remains unknown, as is their exact effect on the measurement result. In this thesis, an investigation into the using the system parameters to evaluate the uncertainty of fringe projection measurements is made. Firstly, a method to localise the centre of ellipses in camera images with an uncertainty is given. This uncertainty is used to derive the uncertainty in the estimated system parameters. The uncertainty in the system parameters is tested by using the system parameters to measure known artefacts, a flatness artefact and two sphere-based artefacts, where the propagated uncertainty is tested against the measurement error. The accuracy of the system parameters are tested by comparing the measurement error of the measurements with measurements made on a commercial system, the GOM ATOS Core 300. In addition, an exhaustive study is undertaken on the calibration, including applying curvature, specificity and parameter stability tests on the non-linear regression used within calibration. The sphere-based measurements were found to not be robust enough against measurement noise in fringe projection to be able to provide information on errors caused by the system parameters. This thesis raises questions as to the appropriateness of using sphere-based measurements to represent the performance of a fringe projection system. The flatness measurements made using the estimated system parameters achieved an accuracy of approximately 30 "μm" across a 300 "mm"×140 "mm" flatness artefact, which is similar to measurements made by the commercial system. However, the estimated uncertainty was unable to explain all measurement discrepancy between the fringe projection measurements and the tactile measurements. The result specificity test indicated poor specificity of the mathematical model of fringe projection, namely the camera pinhole model with Brown-Conrady distortion. It is concluded that the level of accuracy of the mathematical model has become a limiting factor in the accuracy of fringe projection measurements, instead of the accuracy of the inputs to the calibration. Therefore, the uncertainty of the system parameters cannot be used to evaluate an uncertainty of a measurement made using a fringe projection system