Schulich School of Engineering Research & Publications

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Open Access
Assessment of Different Sensor Configurations for Collaborative Driving in Urban Environments
(Hindawi, 2013-01-07) Petovello, Mark G.; Basnayake, Chaminda; O'Keefe, Kyle; Wei, Phil
Vehicle-to-vehicle relative navigation of a network of vehicles travelling in an urban canyon is assessed using least-squares and Kalman filtering covariance simulation techniques. Between-vehicle differential GPS is compared with differential GPS augmented with between-vehicle ultrawideband range and bearing measurements. The three measurement types are combined using both least-squares and Kalman filtering to estimate the horizontal positions of a network of vehicles travelling in the same direction on a road in a simulated urban canyon. The number of vehicles participating in the network is varied between two and nine while the severity of the urban canyon was varied from 15-to 65-degree elevation mask angles. The effect of each vehicle’s azimuth being known a priori, or unknown is assessed. The resulting relative positions in the network of vehicles are then analysed in terms of horizontal accuracy and statistical reliability of the solution. The addition of both range and bearing measurements provides protection levels on the order of 2 m at almost all times where DGPS alone only rarely has observation redundancy and often exhibits estimated accuracies worse than 200 m. Reliability is further improved when the vehicle azimuth is assumed to be known a priori.
Open Access
Automated calibration of mobile cameras for 3D reconstruction of mechanical pipes
(Wiley, 2021-04-06) Maalek, Reza; Lichti, Derek D
This manuscript provides a new framework for calibration of optical instruments, in particular mobile cameras, using highly-redundant circular black and white target fields. New methods were introduced for (i) matching targets between images; (ii) adjusting the systematic eccentricity error of target centers; and (iii) iteratively improving the calibration solution through a free-network self-calibrating bundle adjustment. It was observed that the proposed target matching effectively matched circular targets in 270 mobile phone images, taken from a calibration laboratory, with robustness to Type II errors. The proposed eccentricity adjustment, which requires only camera projective matrices from two views, behaved synonymous to available closed-form solutions, which require several additional object space target information a priori. Finally, specifically for the case of the mobile devices, the calibration parameters obtained using our framework was found superior compared to in-situ calibration for estimating the 3D reconstructed radius of a mechanical pipe (approximately 45% improvement on average).
Open Access
Combining Multichannel RSSI and Vision with Artificial Neural Networks to Improve BLE Trilateration
(MDPI, 2022-06-07) Naghdi, Sharareh; O'Keefe, Kyle
The demands for accurate positioning and navigation applications in complex indoor environments such as emergency call positioning, fire-fighting services, and rescue operations are increasing continuously. Indoor positioning approaches apply different types of sensors to increase the accuracy of the user’s position. Among these technologies, Bluetooth Low Energy (BLE) appeared as a popular alternative due to its low cost and energy efficiency. However, BLE faces challenges related to Received Signal Strength Indicator (RSSI) fluctuations caused by human body shadowing. This work presents a method to compensate RSSI values by applying Artificial Neural Network (ANN) algorithms to RSSI measurements from three BLE advertising channels and a wearable camera as an additional source of information for the presence or absence of human obstacles. The resulting improved RSSI values are then converted into ranges using path loss models, and trilateration is applied to obtain indoor localization. The proposed artificial system provides significantly better localization solutions than fingerprinting or trilateration using uncorrected RSSI values.
Open Access
Comparing Multicarrier Ambiguity Resolution Methods for Geometry-Based GPS and Galileo Relative Positioning and Their Application to Low Earth Orbiting Satellite Attitude Determination
(Hindawi Publishing Corporation, 2009-03-08) O'Keefe, Kyle; Petovello, Mark; Cao, Wei; Lachapelle, Gérard; Guyader, Eric
This paper presents an evaluation of several GNSS multicarrier ambiguity (MCAR) resolution techniques for the purpose of attitude determination of low earth orbiting satellites (LEOs). It is based on the outcomes of the study performed by the University of Calgary and financed by the European 6th Framework Programme for Research and Development as part of the research project PROGENY. The existing MCAR literature is reviewed and eight possible variations of the general MCAR processing scheme are identified based on two possible options for the mathematical model of the float solution, two options for the estimation technique used for the float solution, and finally two possible options for the ambiguity resolution process. The two most promising methods, geometry-based filtered cascading and geometry-based filtered LAMBDA, are analysed in detail for two simulated users modelled after polar orbiting LEOs through an extensive covariance simulation. Both the proposed Galileo constellation and Galileo used in conjunction with the GPS constellation are tested and results are presented in terms of probabilities of correct ambiguity resolution and float and fixed solution baseline accuracies. The LAMBDA algorithm is shown to outperform the cascading method, particularly in the single-frequency dual-GNSS system case. Secondly, more frequencies and multiple GNSS always offer improvement, but the single-frequency dual-system case is found to have similar performance to the dual-frequency single-system case.
Open Access
Detecting and Correcting for Human Obstacles in BLE Trilateration Using Artificial Intelligence
(2020-02-29) Naghdi, Sharareh; O'Keefe, Kyle P. G.
One of the popular candidates in wireless technology for indoor positioning is Bluetooth Low Energy (BLE). However, this technology faces challenges related to Received Signal Strength Indicator (RSSI) fluctuations due to the behavior of the different advertising channels and the effect of human body shadowing among other effects. In order to mitigate these effects, the paper proposes and implements a dynamic Artificial Intelligence (AI) model that uses the three different BLE advertising channels to detect human body shadowing and compensate the RSSI values accordingly. An experiment in an indoor office environment is conducted. 70% of the observations are randomly selected and used for training and the remaining 30% are used to evaluate the algorithm. The results show that the AI model can properly detect and significantly compensate RSSI values for a dynamic blockage caused by a human body. This can significantly improve the RSSI-based ranges and the corresponding positioning accuracies.
Open Access
Environmental Modelling
(2018) Hassan, Quazi K.
This is a lecture note series for the course ENGO 583/ENEN 635 Environmental Modelling. These cover the following topics: nature and purpose of environmental modelling; the top-down and the bottom-up approaches; typology of environmental models; definition of fundamental concepts; steps involved in designing and building a model; calibration, verification and validation of models; scale dependency; sensitivity analysis; characteristics, architecture and functioning of selected environmental models.
Open Access
Evaluation of Selected Mitigation Strategies for Reducing Forest Fire-induced Risk
(2021-12) Ahmed, M. Razu; Rahman, Khan R; Hossain, Sheikh M; Hassan, Quazi K
The aim was to study post-fire perceptions of selected mitigation strategies for wildland fire- induced risks proposed in a previous scientific study for the communities situated within the forested areas. Consequently, we considered engaging relevant professionals in the Regional Municipality of Wood Buffalo (RMWB), Alberta who experienced the costliest wildland fire occurrences in Canadian history known as the 2016 Horse River Fire (HRF). To meet our goal, we formulated a questionnaire based on the scientific evidence presented in a previous study and con-ducted a structured survey. Our results revealed that 24 professionals participated in the survey during the June 2020-April 2021 period, providing a 32% response rate. We observed that a high percentage of the participants agreed (i.e., between 63% and 80%) with the proposed wildland fire-induced risk mitigation strategies, including the presence of no to little vegetation in the 30 m buffer zone from the wildland–urban interface (WUI), extending the 30 m buffer zone to 70 m from the WUI, constructing a 70 m width ring road around the communities, and parking lots of the social infrastructures in the fringe of the communities encountering to the forest. We also found other views, including the use of non-combustible and fire-resistant construction materials, and developing the 70 m buffer zone as a recreational space.
Open Access
Explanation for the seam line discontinuity in terrestrial laser scanner point clouds
(Elsevier, 2019-08) Lichti, Derek D.; Glennie, Craig L.; Al-Durgham, Kaleel; Jahraus, Adam; Steward, Jeremy
The so‐called seam line discontinuity is a phenomenon that can be observed in point clouds captured with some panoramic terrestrial laser scanners. It is an angular discontinuity that is most apparent where the lower limit of the instrument’s angular field‐of‐view intersects the ground. It appears as step discontinuities at the start (0° horizontal direction) and end (180°) of scanning. To the authors’ best knowledge, its cause and its impact, if any, on point cloud accuracy have not yet been reported. This paper presents the results of a rigorous investigation into several hypothesized causes of this phenomenon: differences between the lower and upper elevation angle scanning limits; the presence of a vertical circle index error; and changes in levelling during scanning. New models for the angular observations have been developed and simulations were performed to independently study the impact of each hypothesized cause and to guide the analyses of real datasets. In order to scrutinize each of the hypothesized causes, experiments were conducted with seven real datasets captured with six different instruments: one hybrid‐architecture scanner and five panoramic scanners, one of which was also operated as a hybrid instrument. This study concludes that the difference between the elevation angle scanning limits is the source of the seam line discontinuity phenomenon. Accuracy assessment experiments over real data captured in an indoor test facility demonstrate that the seam line discontinuity has no metric impact on the point clouds.
Open Access
Geometric modelling and calibration of a spherical camera imaging system
(2020-04-16) Lichti, Derek D.; Jarron, David; Tredoux, Wynand; Shahbazi, Mozhdeh M.; Radovanovic, Robert
The Ladybug5 is an integrated, multi-camera system that features a near-spherical field of view. It is commonly deployed on mobile mapping systems to collect imagery for 3D reality capture. This paper describes an approach for the geometric modelling and self-calibration of this system. The collinearity equations of the pinhole camera model are augmented with five radial lens distortion terms to correct the severe barrel distortion. Weighted relative orientation stability constraints are added to the self-calibrating bundle adjustment solution to enforce the angular and positional stability between the Ladybug5’s six cameras. Results are presented from two calibration data-sets and an independent data-set for accuracy assessment. It is demonstrated that centimetre-level 3D reconstruction accuracy can be achieved with the proposed approach. Moreover, the effectiveness of the lens distortion modelling is demonstrated. Image-space precision and object-space accuracy are improved by 92% and 93%, respectively, relative to a two-term model. The high correlations between lens distortion coefficients were not found to be detrimental to the solution. The mechanical stability of the system was assessed by comparing calibrations taken before and after ten months of routine camera system use. The results suggest sub-pixel interior orientation stability and millimetre-level relative orientation stability. Analyses of accuracy and parameter correlation demonstrate that a slightly-relaxed weighting strategy is preferred to tightly-enforced relative orientation stability constraints.
Open Access
GNSS Code Multipath Mitigation by Cascading Measurement Monitoring Techniques
(2018-06-19) Pirsiavash, Ali; Broumandan, Ali; Lachapelle, Gérard; O'Keefe, Kyle P. G.
Various measurement monitoring techniques are investigated to mitigate the effect of global navigation satellite systems (GNSS) code multipath through error correction, stochastic weighting of measurements and detection and exclusion (or de-weighting) of affected measurements. Following a comprehensive review of each approach, the paper focuses on detection/exclusion and detection/de-weighting techniques where several single and dual-frequency monitoring metrics are employed in a combination with time-averaging and the M of N detection strategy. A new Geometry-Free (GF) detection metric is proposed given its capability to be combined with a preceding Code-Minus-Carrier (CMC)-based error correction to reduce the number of excluded or de-weighted measurements and thus preserve the measurement geometry. Three geometry-based algorithms, namely measurement subset testing, consecutive exclusion and iterative change of measurement weights are investigated to address multipath scenarios with multiple simultaneously affected measurements. Experimental results are provided using GPS L1, L2C and L5 data collected in multipath environments for static and kinematic scenarios. For GPS L1, the proposed combined method shows more than 38% improvement over a conventional Carrier-to-Noise-density ratio (C/N₀)-based Least-Squares (LS) solution in all but deep urban canyons. Lower performance was observed for L2C and L5 frequencies with a limited number of satellites in view.
Open Access
GNSS Signal and Measurement Quality Monitoring for Multipath Detection and Mitigation
(2019-08) Pirsiavash, Ali
Receiver level Global Navigation Satellite Systems (GNSS) Signal and Measurement Quality Monitoring (SQM and MQM) to detect and de-weight measurements distorted by multipath are investigated. SQM and MQM monitoring metrics are defined at the tracking and measurement levels of the receiver; a new geometry-based de-weighting technique is developed. Following an analytical discussion of the sensitivity and effectiveness of the metrics, field data analysis is provided for static and kinematic modes to verify practical performance. Results obtained for the designed SQM and MQM-based detection metrics show reliable performance of 3 to 5 m Minimum Detectable Multipath Error (MDME). Although limited by multipath characteristics and measurement geometry, when detected faulty measurements are de-weighted, positioning performance improves by up to 53% for different multipath scenarios.
Open Access
GPS-Assisted Path Loss Exponent Estimation for Positioning in IEEE 802.11 Networks
(Hindawi Publishing Corporation, 2013-01) Navarro-Alvarez, Ernesto; Siller, Mario; O'Keefe, Kyle P.G.
We present a new adaptive method to calculate the path loss exponent (PLE) for microcell outdoor dynamic environments in the 2.4 GHz Industrial, Scientific, and Medical (ISM) frequency band. The proposed method calculates the PLE during random walks by recording signal strength measurements from Radio Frequency (RF) transceivers and position data with a consumer-grade GPS receiver. The novelty of this work lies in the formulation of signal propagation conditions as a parametric observation model in order to estimate first the PLE and then the distance from the received RF signals using nonlinear least squares. GPS data is used to identify long term fading from the received signal's power and helps to refine the power-distance model. Ray tracing geometries for urban canyon (direct line of sight) and nonurban canyon (obstacles) propagation scenarios are used as the physics of the model (design matrix). Although the method was implemented for a lightweight localization algorithm for the 802.11b/g (Wi-Fi) standard, it can also be applied to other ISM band protocols such as 802.15.4 (Zigbee) and 802.15.1 (Bluetooth).
Open Access
Kinematic Zenith Tropospheric Delay Estimation with GNSS PPP in Mountainous Areas
(MDPI, 2021-08-25) Gratton, Paul; Banville, Simon; Lachapelle, Gérard; O’Keefe, Kyle
The use of global navigation satellite systems (GNSS) precise point positioning (PPP) to estimate zenith tropospheric delay (ZTD) profiles in kinematic vehicular mode in mountainous areas is investigated. Car-mounted multi-constellation GNSS receivers are employed. The Natural Resources Canada Canadian Spatial Reference System PPP (CSRS-PPP) online service that currently processes dual-frequency global positioning system (GPS) and Global’naya Navigatsionnaya Sputnikovaya Sistema (GLONASS) measurements and is now capable of GPS integer ambiguity resolution is used. An offline version that can process the above and Galileo measurements simultaneously, including Galileo integer ambiguity resolution is also tested to evaluate the advantage of three constellations. A multi-day static data set observed under open sky is first tested to determine performance under ideal conditions. Two long road profile tests conducted in kinematic mode are then analyzed to assess the capability of the approach. The challenges of ZTD kinematic profiling are numerous, namely shorter data sets, signal shading due to topography and forests of conifers along roads, and frequent losses of phase lock requiring numerous but not always successful integer ambiguity re-initialization. ZTD profiles are therefore often only available with float ambiguities, reducing system observability. Occasional total interruption of measurement availability results in profile discontinuities. CSRS-PPP outputs separately the zenith hydrostatic or dry delay (ZHD) and water vapour content or zenith wet delay (ZWD). The two delays are analyzed separately, with emphasis on the more unpredictable and highly variable ZWD, especially in mountainous areas. The estimated delays are compared with the Vienna Mapping Function 1 (VMF1), which proves to be highly effective to model the large-scale profile variations in the Canadian Rockies, the main contribution of GNSS PPP being the estimation of higher frequency ZWD components. Of the many conclusions drawn from the field experiments, it is estimated that kinematic profiles are generally determined with accuracy of 10 to 20 mm, depending on the signal harshness of the environment.
Open Access
Linear regression with an observation distribution model
(Springer, 2021-01-18) Lichti, Derek D; Chan, Ting On; Belton, David
Despite the high complexity of the real world, linear regression still plays an important role in estimating parameters to model a physical relationship between at least two variables. The precision of the estimated parameters, which can usually be considered as an indicator of the solution quality, is conventionally obtained from the inverse of the normal equations matrix for which intensive computation is required when the number of observations is large. In addition, the impacts of the distribution of the observations on parameter precision are rarely reported in the literature. In this paper, we propose a new methodology to model the distribution of observations for linear regression in order to predict the parameter precision prior to actual data collection and performing the regression. The precision analysis can be readily performed given a hypothesized data distribution. The methodology has been verified with several simulated and real datasets. The results show that the empirical and model-predicted precisions match very well, with discrepancies of up to 6% and 3.4% for simulated and real datasets, respectively. Simulations demonstrate that these differences are simply due to finite sample size. In addition, simulation also demonstrates the relative insensitivity of the method to noise in the independent regression variables that causes deviations from the data distribution function. The proposed methodology allows straightforward prediction of the parameter precision based on the distribution of the observations related to their numerical limits and geometry, which greatly simplify design procedures for various experimental setups commonly involved in geodetic surveying such as LiDAR data collection.
Open Access
Modelling Extreme Wide-Angle Lens Cameras
(Wiley, 2021-12-01) Lichti, Derek D; Tredoux, Wynand; Maalek, Reza; Helmholz, Petra; Radovanovic, Robert
The use of consumer cameras fitted with extreme wide angle (EWA) lenses for photogrammetric measurement is increasing. Conventional modelling of EWA systems relies on the pinhole camera model and up to five radial lens distortion terms. Aiming to reduce model complexity, this paper reports an investigation into an alternate approach using fisheye lens models for EWA systems, despite them not falling strictly into to the fisheye category. Four fisheye models were tested on four different cameras under laboratory conditions. The self-calibration results show superior model fit for all fisheye models over the pinhole plus radial model in terms of residual RMS. The number radial distortion of terms required for the fisheye models was lower in all cases, so model complexity was reduced. Independent assessment revealed very similar 3D reconstruction accuracy for all models. The results suggest that fisheye modelling is an advantageous alternative for EWA lens systems.
Open Access
New approach for low-cost TLS target measurement
(ASCE, 2019-08) Lichti, Derek D.; Glennie, Craig L.; Jahraus, Adam; Hartzell, Preston J.
The registration and calibration of data captured with terrestrial laser scanner instruments can be effectively achieved using signalized targets comprising components of both high and low reflectivity, so-called contrast targets. For projects requiring tens or even hundreds of such targets, the cost of manufacturer-constructed targets can be prohibitive. Moreover, the details of proprietary target center co-ordinate measurement algorithms are often not available to users. This paper reports on the design of a low-cost contrast target using readily-available materials and an accompanying center measurement algorithm. Their compatibility with real terrestrial laser scanner data was extensively tested on six different instruments: two Faro Focus 3D scanners; a Leica HDS6100; a Leica P40; a Riegl VZ-400; and a Zoller+Fröhlich Imager 5010. Repeatability was examined as a function of range, incidence angle, sampling resolution, target intensity and target contrast. Performance in system self-calibration and from independent accuracy assessment is also reported. The results demonstrate compatibility for all five scanners. However, all datasets except the Faro Focus 3D require exclusion of observations made at high incidence angles in order to prevent range biases. Results also demonstrate that the spectral reflectivity of the target components is critical to ensure high contrast between target components and, therefore, high-quality target center co-ordinate measurements.
Open Access
New Confocal Hyperbola-based Ellipse Fitting with Applications to Estimating Parameters of Mechanical Pipes from Point Clouds
(University of Calgary, 2021-03-14) Maalek, Reza; Lichti, Derek D
This manuscript presents a new method for fitting ellipses to two-dimensional data using the confocal hyperbola approximation to the geometric distance of points to ellipses. The proposed method was evaluated and compared to established methods on simulated and real-world datasets. First, it was revealed that the confocal hyperbola distance considerably outperforms other distance approximations such as algebraic and Sampson. Next, the proposed ellipse fitting method was compared with five reliable and established methods proposed by Halir, Taubin, Kanatani, Ahn and Szpak. The performance of each method as a function of rotation, aspect ratio, noise, and arclength were examined. It was observed that the proposed ellipse fitting method achieved almost identical results (and in some cases better) than the gold standard geometric method of Ahn and outperformed the remaining methods in all simulation experiments. Finally, the proposed method outperformed the considered ellipse fitting methods in estimating the geometric parameters of cylindrical mechanical pipes from point clouds. The results of the experiments show that the confocal hyperbola is an excellent approximation to the true geometric distance and produces reliable and accurate ellipse fitting in practical settings.
Open Access
New method for first-order network design applied to TLS self-calibration networks
(Elsevier, 2021-07-01) Lichti, Derek D; Pexman, Kate; Tredoux, Wynand
Terrestrial laser scanning (TLS) is established as a viable means for precision measurement and the need for systematic error modelling and instrument self-calibration is well recognized. While additional parameter (AP) models and procedures for their estimation from signalized target fields have been developed, the first-order design (FOD) of TLS self-calibration networks remains an active area of research aiming to improve AP quality. The conventional FOD approach of numerical simulation carries a heavy computational burden. This paper reports a new method for TLS self-calibration FOD that avoids the high computational effort and can predict AP precision in closed form. Its basis is a relatively simple analytical model of the distribution of spherical coordinate observations, specifically the elevation angle. The accuracy of predicted AP precision is quantified by comparison of precision estimates from a more complex and detailed observation distribution model and from self-calibration. Results from 25 datasets demonstrate the high accuracy (arc second or better) of the closed-form approach. A new observation distribution model is then developed to optimize the geometric design of TLS self-calibration networks. An ideal observation distribution based on the versine function and a corresponding target field configuration that enhance AP precision are established. Testing was performed on five additional, very dense TLS self-calibration datasets. Each dataset was subsampled so as to replicate the observation distributions corresponding to conventional network design and the proposed design. The results show that up to 55% improvement in AP precision, obtained from self-calibration, can be achieved with the new design and these results agree with versine-distribution model predictions within 14% to 16%.
Open Access
Remote Sensing of Wildland Fire-induced Risk Assessment Framework
(National Fire Information Database (NFID) Project, 2017-12) Hassan, Quazi K.; Ahmed, M. Razu; Rahaman, Khan Rubayet
Wildland fire is one of the critical natural hazards that pose a significant threat to the communities located in the vicinity of forested/vegetated areas. In this report, our overall goal was to use very high spatial resolution (0.5-2.4m) satellite images to develop wildland fire-induced risk framework. We considered two extreme fire events, such as the 2016 HRF over Fort McMurray, and 2011 Lesser Slave Lake fire in Alberta. Thus, our activities included the: (i) estimation of the structural damages; and (ii) delineation of the wildland-urban interface (WUI) and its associated buffers at certain intervals, and their utilization in assessing potential risks. Our proposed method of remote sensing-based estimates was compared with the ground-based information available from the Planning and Development Recovery Committee Task Force of Regional Municipality of Wood Buffalo (RMWB) and National Fire Information Database (NFID); and found strong linear relationships (i.e., r2-value of 0.97 with a slope of 0.97 for the 2016 HRF over Fort McMurray; and 378 from satellite image vs. 407 from 378 from satellite image vs. 407 from NFID system for the 2011 Lesser Slave Lake fire). Upon delineating the WUI and its associated buffer zones at 10m, 30m, 50m, 70m and 100m distances; we found existence of vegetation within the 30m buffers from the WUI for all of the damaged structures. In addition, we noticed that the relevant authorities had removed vegetation in some areas between 30m and 70m buffers from the WUI in case of Fort McMurray area, which was proven to be effective in order to protect the structures in the adjacent communities. Furthermore, we mapped the wildland fire-induced vulnerable areas upon considering the WUI and its associated buffers. We found that there were still some communities that had the existence of vegetation within the buffer zones; thus such vegetation should be removed and monitored regularly in order to reduce the wildland fire-induced risks.
Open Access
Robust Detection of Non-overlapping Ellipses from Points with Applications to Circular Target Extraction in Images and Cylinder Detection in Point Clouds
(Elsevier, 2021-04-14) Maalek, Reza; Lichti, Derek D
Detection of non-overlapping ellipses from 2-dimensional (2D) edge points is an essential step towards solving typical photogrammetry problems pertaining to feature detection, calibration, and registration of optical instruments. For instance, circular and spherical black and white calibration and registration targets are represented as ellipses in images. Furthermore, the intersection of a cut plane with cylindrical point clouds generates 2D points following elliptic patterns. To this end, this study proposes a collection of new methods for the automatic and robust detection of non-overlapping ellipses from 2D points. These methods will first be applied to detect circular and spherical targets in images and, second, to detect cylinders in 3D point clouds. The method utilizes the Euclidian ellipticity and a new systematic and generalizable threshold to decide if a set of connected points follow an elliptic pattern. When connected points include outliers, the newly proposed robust Monte Carlo-based ellipse fitting method will be deployed. This method includes three new developments: (i) selecting initial subsamples using a bucketing strategy based on the polar angle of the points; (ii) detecting inlier points by reducing the robust ellipse fitting to a robust circle fitting problem; and (iii) choosing the best inlier set amongst all subsamples using adaptive, systematic, and generalizable selection criteria. A new process is presented to extract cylinders from a point cloud by detecting non-overlapping ellipses from the points projected onto an intersecting cut plane. The proposed methods were compared to established state-of-the-art methods, using simulated and real-world datasets, through the design of four sets of original experiments. The experiments include (i) comparisons of robust ellipse fitting; (ii) sensitivity analysis of the ellipse validation criteria; (iii) comparison of non-overlapping ellipse detection; and (iv) detection of pipes from terrestrial laser scanner point clouds. It was found that the proposed robust ellipse detection was superior to four reliable robust methods, including the popular least median of squares, in both simulated and real-world datasets. The proposed process for detecting non-overlapping ellipses achieved F-measure of 99.3% on real images, compared to 42.4%, 65.6%, and 59.2%, obtained using the methods of Fornaciari, Patraucean, and Panagiotakis, respectively. The proposed cylinder extraction method identified all detectable mechanical pipes in two real-world point clouds collected in laboratory and industrial construction site conditions. The results of this investigation show promise for the application of the proposed methods for automatic extraction of circular targets from images and pipes from point clouds.