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Papers by Angel Ivan Garcia Moreno

Research paper thumbnail of Automatic 3D City Reconstruction Platform Using a LIDAR and DGPS

Research paper thumbnail of Dynamic multi-sensor platform for efficient 3D-digitalization of cities

Journal of Computing and Information Science in Engineering

Three-dimensional urban reconstruction requires the combination of data from different sensors, s... more Three-dimensional urban reconstruction requires the combination of data from different sensors, such as cameras, inertial systems, GPS and laser sensors. In this technical report, a complete system for the generation of textured volumetric global maps (deep vision) is presented. Our acquisition platform is terrestrial and moves through different urban environments digitizing them. The report is focused on describing the 3 main problems identified in this type of works. (1) The acquisition of three-dimensional data with high precision, (2) the extraction of the texture and its correlation with the 3D data and (3) the generation of the surfaces that describe the components of the urban environment. It also describes the methods implemented to extrinsically calibrate the acquisition platform, as well as the methods developed to eliminate the radial and tangential image distortion; and the subsequent generation of a panoramic image. Procedures are developed for the sampling of 3d data a...

Research paper thumbnail of Dynamic set point model for driver alert state using digital image processing

Multimedia Tools and Applications

Research paper thumbnail of Complete sensitivity analysis in a LIDAR-camera calibration model

Journal of Computing and Information Science in Engineering, 2015

This paper presents a sensitivity analysis in the calibration of two sensors: a laser sensor Velo... more This paper presents a sensitivity analysis in the calibration of two sensors: a laser sensor Velodyne HDL-64E and a panoramic camera Point Grey Ladybug2; both sensors are used for three-dimensional urban reconstruction and were calibrated by two techniques; their results are compared in the sensitivity analysis. The effect of each parameter on the errors propagated in our platform reconstruction was analyzed using the simulated and experimental data sets. To compare the calibration parameters, we implement simulation techniques like Monte Carlo (MC) and Latin hypercube sampling (LHS). The sensitivity index for each parameter was calculated by two methods. The Sobol method, which is based on the analysis of the variance breakdown and the Fourier amplitude sensitivity test (FAST) method, based on Fourier analysis. Measures of variability on the simulated and experimental calibration parameters are shown for the calibration techniques implemented. Results on parameters and factors caus...

Research paper thumbnail of Three-dimensional terrestrial reconstruction system: Calibration and error propagation approach

2015 38th International Conference on Telecommunications and Signal Processing (TSP), 2015

Research paper thumbnail of Detección de Automóviles en Escenarios Urbanos Escaneados por un Lidar

Revista Iberoamericana de Automática e Informática Industrial RIAI, 2015

Research paper thumbnail of Generación de mapas globales 3D a partir de mapas locales 3D

Research paper thumbnail of LIDAR and Panoramic Camera Extrinsic Calibration Approach Using a Pattern Plane

Lecture Notes in Computer Science, 2013

Research paper thumbnail of GPS Precision Time Stamping for the HDL-64E Lidar Sensor and Data Fusion

2012 IEEE Ninth Electronics, Robotics and Automotive Mechanics Conference, 2012

ABSTRACT 3D reconstruction of large scale areas was created by merging real world information fro... more ABSTRACT 3D reconstruction of large scale areas was created by merging real world information from different sensors, this is an important issue in multimedia research. In this paper, we propose an efficient construction of urban scenes from LIDAR data. The system is composed of a Velodyne LIDAR 64E and a differential GPS. The sensors are synchronized through their internal clocks, and the position of the LIDAR acquisition is given by the GPS data. In this work, we computed the position using plane geodetic UTM (Universal Transverse Mercator) coordinates by Cotticchia-Surace algorithm which allows us to obtain centimeter accuracy. The translation vector between acquisitions is computed using the GPS position, and the rotation matrix is computed using the planes extracted from the environment. The results show a 3D reconstruction of large scale city.

Research paper thumbnail of Mobile remote sensing platform: An uncertainty calibration analysis

2014 11th International Joint Conference on Computer Science and Software Engineering (JCSSE), 2014

Research paper thumbnail of Sensitivity Analysis in a Lidar-Camera Calibration

Computer Science & Information Technology ( CS & IT ), 2015

In this paper, variability analysis was performed on the model calibration methodology between a ... more In this paper, variability analysis was performed on the model calibration methodology between a multi-camera system and a LiDAR laser sensor (Light Detection and Ranging). Both sensors are used to digitize urban environments. A practical and complete methodology is presented to predict the error propagation inside the LiDAR-camera calibration. We perform a sensitivity analysis in a local and global way. The local approach analyses the output variance with respect to the input, only one parameter is varied at once. In the global sensitivity approach, all parameters are varied simultaneously and sensitivity indexes are calculated on the total variation range of the input parameters. We quantify the uncertainty behaviour in the intrinsic camera parameters and the relationship between the noisy data of both sensors and their calibration. We calculated the sensitivity indexes by two techniques, Sobol and FAST (Fourier amplitude sensitivity test). Statistics of the sensitivity analysis are displayed for each sensor, the sensitivity ratio in laser-camera calibration data

Research paper thumbnail of Error propagation and uncertainty analysis between 3D laser scanner and camera

In this work we present an in-situ method to compute the calibration of two sensors, a LIDAR (Lig... more In this work we present an in-situ method to compute the calibration of two sensors, a LIDAR (Light Detection and Ranging) and a spherical camera. Both sensors are used in urban environment reconstruction tasks. In this scenario the speed at which the various sensors acquire and merge the information is very important; however reconstruction accuracy, which depends on sensors calibration, is also of high relevance. Here, a new calibration pattern, visible to both sensors is proposed. By this means, the correspondence between each laser point and its position in the camera image is obtained so that the texture and color of each LIDAR point can be known. Experimental results for the calibration and uncertainty analysis are presented for data collected by the platform integrated with a LIDAR and a spherical camera.

Research paper thumbnail of Complete Sensitivity Analysis in a LiDAR-Camera Calibration Model

This paper presents a sensitivity analysis in the calibration of two sensors: a laser sensor Velo... more This paper presents a sensitivity analysis in the calibration of two sensors: a laser sensor Velodyne HDL-64E and a panoramic camera Point Grey Ladybug2; both sensors are used for three-dimensional urban reconstruction and were calibrated by two techniques; their results are compared in the sensitivity analysis. The effect of each parameter on the errors propagated in our platform reconstruction was analyzed using the simulated and experimental data sets. To compare the calibration parameters, we implement simulation techniques like Monte Carlo (MC) and Latin hypercube sampling (LHS). The sensitivity index for each parameter was calculated by two methods. The Sobol method, which is based on the analysis of the variance breakdown and the Fourier amplitude sensitivity test (FAST) method, based on Fourier analysis. Measures of variability on the simulated and experimental calibration parameters are shown for the calibration techniques implemented. Results on parameters and factors causing higher uncertainty in the calibration process are presented.

Research paper thumbnail of Error propagation and uncertainty analysis between 3D laser scanner and camera

In this work we present an in-situ method to compute the calibration of two sensors, a LIDAR (Lig... more In this work we present an in-situ method to compute the calibration of two sensors, a LIDAR (Light Detection and Ranging) and a spherical camera. Both sensors are used in urban environment reconstruction tasks. In this scenario the speed at which the various sensors acquire and merge the information is very important, however reconstruction accuracy, which depends on sensors calibration, is also of high relevance. Here, a new calibration pattern, visible to both sensors is proposed. By this mean, the correspondence between each laser point and its position in the camera image is obtained so that the texture and color of each LIDAR point can be known. Experimental results for the calibration and uncertainty analysis are presented for data collected by the platform integrated with a LIDAR and the spherical camera.

Research paper thumbnail of Detection and Segmentation of 3D Objects in Urban Environments Using Indexation

IEEE Latin America Transactions, 2015

ABSTRACT A procedure for automobile detection on 3D point clouds of urban areas is presented in t... more ABSTRACT A procedure for automobile detection on 3D point clouds of urban areas is presented in this work. Point clouds are obtained using an HDL-64E Velodyne LIDAR. The work is divided into two sections: Segmentation, in which the base plane (floor) and its perpendicular planes are extracted using Hough's technique. Next every other object is segmented using MeanShift method; and Indexation, in which all segmented objects are modeled according to a normal direction so that its histograms can be obtained and compared to a pre-loaded histogram database. The reconstructed environment is considered to be semi-structured, meaning that it can be modeled using planes. In the process ROC analysis is used for thresholds optimization.

Research paper thumbnail of SENSITIVITY ANALYSIS IN A LIDARCAMERA CALIBRATION

In this paper, variability analysis was performed on the model calibration methodology between a ... more In this paper, variability analysis was performed on the model calibration methodology between a multi-camera system and a LiDAR laser sensor (Light Detection and Ranging). Both sensors are used to digitize urban environments. A practical and complete methodology is presented to predict the error propagation inside the LiDAR-camera calibration. We perform a sensitivity analysis in a local and global way. The local approach analyses the output variance with respect to the input, only one parameter is varied at once. In the global sensitivity approach, all parameters are varied simultaneously and sensitivity indexes are calculated on the total variation range of the input parameters. We quantify the uncertainty behaviour in the intrinsic camera parameters and the relationship between the noisy data of both sensors and their calibration. We calculated the sensitivity indexes by two techniques, Sobol and FAST (Fourier amplitude sensitivity test). Statistics of the sensitivity analysis are displayed for each sensor, the sensitivity ratio in laser-camera calibration data

Research paper thumbnail of Automatic 3D City Reconstruction Platform Using a LIDAR and DGPS

Research paper thumbnail of Dynamic multi-sensor platform for efficient 3D-digitalization of cities

Journal of Computing and Information Science in Engineering

Three-dimensional urban reconstruction requires the combination of data from different sensors, s... more Three-dimensional urban reconstruction requires the combination of data from different sensors, such as cameras, inertial systems, GPS and laser sensors. In this technical report, a complete system for the generation of textured volumetric global maps (deep vision) is presented. Our acquisition platform is terrestrial and moves through different urban environments digitizing them. The report is focused on describing the 3 main problems identified in this type of works. (1) The acquisition of three-dimensional data with high precision, (2) the extraction of the texture and its correlation with the 3D data and (3) the generation of the surfaces that describe the components of the urban environment. It also describes the methods implemented to extrinsically calibrate the acquisition platform, as well as the methods developed to eliminate the radial and tangential image distortion; and the subsequent generation of a panoramic image. Procedures are developed for the sampling of 3d data a...

Research paper thumbnail of Dynamic set point model for driver alert state using digital image processing

Multimedia Tools and Applications

Research paper thumbnail of Complete sensitivity analysis in a LIDAR-camera calibration model

Journal of Computing and Information Science in Engineering, 2015

This paper presents a sensitivity analysis in the calibration of two sensors: a laser sensor Velo... more This paper presents a sensitivity analysis in the calibration of two sensors: a laser sensor Velodyne HDL-64E and a panoramic camera Point Grey Ladybug2; both sensors are used for three-dimensional urban reconstruction and were calibrated by two techniques; their results are compared in the sensitivity analysis. The effect of each parameter on the errors propagated in our platform reconstruction was analyzed using the simulated and experimental data sets. To compare the calibration parameters, we implement simulation techniques like Monte Carlo (MC) and Latin hypercube sampling (LHS). The sensitivity index for each parameter was calculated by two methods. The Sobol method, which is based on the analysis of the variance breakdown and the Fourier amplitude sensitivity test (FAST) method, based on Fourier analysis. Measures of variability on the simulated and experimental calibration parameters are shown for the calibration techniques implemented. Results on parameters and factors caus...

Research paper thumbnail of Three-dimensional terrestrial reconstruction system: Calibration and error propagation approach

2015 38th International Conference on Telecommunications and Signal Processing (TSP), 2015

Research paper thumbnail of Detección de Automóviles en Escenarios Urbanos Escaneados por un Lidar

Revista Iberoamericana de Automática e Informática Industrial RIAI, 2015

Research paper thumbnail of Generación de mapas globales 3D a partir de mapas locales 3D

Research paper thumbnail of LIDAR and Panoramic Camera Extrinsic Calibration Approach Using a Pattern Plane

Lecture Notes in Computer Science, 2013

Research paper thumbnail of GPS Precision Time Stamping for the HDL-64E Lidar Sensor and Data Fusion

2012 IEEE Ninth Electronics, Robotics and Automotive Mechanics Conference, 2012

ABSTRACT 3D reconstruction of large scale areas was created by merging real world information fro... more ABSTRACT 3D reconstruction of large scale areas was created by merging real world information from different sensors, this is an important issue in multimedia research. In this paper, we propose an efficient construction of urban scenes from LIDAR data. The system is composed of a Velodyne LIDAR 64E and a differential GPS. The sensors are synchronized through their internal clocks, and the position of the LIDAR acquisition is given by the GPS data. In this work, we computed the position using plane geodetic UTM (Universal Transverse Mercator) coordinates by Cotticchia-Surace algorithm which allows us to obtain centimeter accuracy. The translation vector between acquisitions is computed using the GPS position, and the rotation matrix is computed using the planes extracted from the environment. The results show a 3D reconstruction of large scale city.

Research paper thumbnail of Mobile remote sensing platform: An uncertainty calibration analysis

2014 11th International Joint Conference on Computer Science and Software Engineering (JCSSE), 2014

Research paper thumbnail of Sensitivity Analysis in a Lidar-Camera Calibration

Computer Science & Information Technology ( CS & IT ), 2015

In this paper, variability analysis was performed on the model calibration methodology between a ... more In this paper, variability analysis was performed on the model calibration methodology between a multi-camera system and a LiDAR laser sensor (Light Detection and Ranging). Both sensors are used to digitize urban environments. A practical and complete methodology is presented to predict the error propagation inside the LiDAR-camera calibration. We perform a sensitivity analysis in a local and global way. The local approach analyses the output variance with respect to the input, only one parameter is varied at once. In the global sensitivity approach, all parameters are varied simultaneously and sensitivity indexes are calculated on the total variation range of the input parameters. We quantify the uncertainty behaviour in the intrinsic camera parameters and the relationship between the noisy data of both sensors and their calibration. We calculated the sensitivity indexes by two techniques, Sobol and FAST (Fourier amplitude sensitivity test). Statistics of the sensitivity analysis are displayed for each sensor, the sensitivity ratio in laser-camera calibration data

Research paper thumbnail of Error propagation and uncertainty analysis between 3D laser scanner and camera

In this work we present an in-situ method to compute the calibration of two sensors, a LIDAR (Lig... more In this work we present an in-situ method to compute the calibration of two sensors, a LIDAR (Light Detection and Ranging) and a spherical camera. Both sensors are used in urban environment reconstruction tasks. In this scenario the speed at which the various sensors acquire and merge the information is very important; however reconstruction accuracy, which depends on sensors calibration, is also of high relevance. Here, a new calibration pattern, visible to both sensors is proposed. By this means, the correspondence between each laser point and its position in the camera image is obtained so that the texture and color of each LIDAR point can be known. Experimental results for the calibration and uncertainty analysis are presented for data collected by the platform integrated with a LIDAR and a spherical camera.

Research paper thumbnail of Complete Sensitivity Analysis in a LiDAR-Camera Calibration Model

This paper presents a sensitivity analysis in the calibration of two sensors: a laser sensor Velo... more This paper presents a sensitivity analysis in the calibration of two sensors: a laser sensor Velodyne HDL-64E and a panoramic camera Point Grey Ladybug2; both sensors are used for three-dimensional urban reconstruction and were calibrated by two techniques; their results are compared in the sensitivity analysis. The effect of each parameter on the errors propagated in our platform reconstruction was analyzed using the simulated and experimental data sets. To compare the calibration parameters, we implement simulation techniques like Monte Carlo (MC) and Latin hypercube sampling (LHS). The sensitivity index for each parameter was calculated by two methods. The Sobol method, which is based on the analysis of the variance breakdown and the Fourier amplitude sensitivity test (FAST) method, based on Fourier analysis. Measures of variability on the simulated and experimental calibration parameters are shown for the calibration techniques implemented. Results on parameters and factors causing higher uncertainty in the calibration process are presented.

Research paper thumbnail of Error propagation and uncertainty analysis between 3D laser scanner and camera

In this work we present an in-situ method to compute the calibration of two sensors, a LIDAR (Lig... more In this work we present an in-situ method to compute the calibration of two sensors, a LIDAR (Light Detection and Ranging) and a spherical camera. Both sensors are used in urban environment reconstruction tasks. In this scenario the speed at which the various sensors acquire and merge the information is very important, however reconstruction accuracy, which depends on sensors calibration, is also of high relevance. Here, a new calibration pattern, visible to both sensors is proposed. By this mean, the correspondence between each laser point and its position in the camera image is obtained so that the texture and color of each LIDAR point can be known. Experimental results for the calibration and uncertainty analysis are presented for data collected by the platform integrated with a LIDAR and the spherical camera.

Research paper thumbnail of Detection and Segmentation of 3D Objects in Urban Environments Using Indexation

IEEE Latin America Transactions, 2015

ABSTRACT A procedure for automobile detection on 3D point clouds of urban areas is presented in t... more ABSTRACT A procedure for automobile detection on 3D point clouds of urban areas is presented in this work. Point clouds are obtained using an HDL-64E Velodyne LIDAR. The work is divided into two sections: Segmentation, in which the base plane (floor) and its perpendicular planes are extracted using Hough's technique. Next every other object is segmented using MeanShift method; and Indexation, in which all segmented objects are modeled according to a normal direction so that its histograms can be obtained and compared to a pre-loaded histogram database. The reconstructed environment is considered to be semi-structured, meaning that it can be modeled using planes. In the process ROC analysis is used for thresholds optimization.

Research paper thumbnail of SENSITIVITY ANALYSIS IN A LIDARCAMERA CALIBRATION

In this paper, variability analysis was performed on the model calibration methodology between a ... more In this paper, variability analysis was performed on the model calibration methodology between a multi-camera system and a LiDAR laser sensor (Light Detection and Ranging). Both sensors are used to digitize urban environments. A practical and complete methodology is presented to predict the error propagation inside the LiDAR-camera calibration. We perform a sensitivity analysis in a local and global way. The local approach analyses the output variance with respect to the input, only one parameter is varied at once. In the global sensitivity approach, all parameters are varied simultaneously and sensitivity indexes are calculated on the total variation range of the input parameters. We quantify the uncertainty behaviour in the intrinsic camera parameters and the relationship between the noisy data of both sensors and their calibration. We calculated the sensitivity indexes by two techniques, Sobol and FAST (Fourier amplitude sensitivity test). Statistics of the sensitivity analysis are displayed for each sensor, the sensitivity ratio in laser-camera calibration data