The Experts below are selected from a list of 54 Experts worldwide ranked by ideXlab platform
M. A. Sotelo - One of the best experts on this subject based on the ideXlab platform.
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Parking Assistance System for Leaving Perpendicular Parking Lots: Experiments in Daytime\/Nighttime Conditions
IEEE Intelligent Transportation Systems Magazine, 2014Co-Authors: David Fernández-llorca, Iván García-daza, Agustín Martínez-hellín, Sergio Álvarez-pardo, M. A. SoteloAbstract:Backing-out and heading-out maneuvers in perpendicular or angle parking lots are one of the most dangerous maneuvers, especially in cases where side parked cars block the driver view of the potential traffic flow. In this paper, a new vision-based Advanced Driver Assistance System (ADAS) is proposed to automatically warn the driver in such scenarios. A monocular grayscale camera was installed at the back-right side of a vehicle. A Finite State Machine (FSM) defined according to three CAN Bus variables and a manual signal provided by the user is used to handle the activation/deactivation of the detection module. The proposed oncoming traffic detection module computes spatio-temporal images from a set of predefined scan-lines which are related to the position of the road. A novel spatio-temporal motion descriptor is proposed (STHOL) accounting for the number of lines, their orientation and length of the spatio-temporal images. Some parameters of the proposed descriptor are adapted for nighttime conditions. A Bayesian framework is then used to trigger the warning signal using multivariate Normal Density Functions. Experiments are conducted on image data captured from a vehicle parked at different location of an urban environment, including both daytime and nighttime lighting conditions. We demonstrate that the proposed approach provides robust results maintaining processing rates close to real time.
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Vision-based parking assistance system for leaving perpendicular and angle parking lots
2013 IEEE Intelligent Vehicles Symposium (IV), 2013Co-Authors: D. F. Llorca, S. Álvarez, M. A. SoteloAbstract:Backing-out maneuvers in perpendicular or angle parking lots are one of the most dangerous maneuvers, specially in cases where side parked cars block the driver view of the potential traffic flow. In this paper a new vision-based Advanced Driver Assistance System (ADAS) is proposed to automatically warn the driver in such scenarios. A monocular gray-scale camera is installed at the back-right side of the vehicle. A Finite State Machine (FSM) defined according to three CAN-Bus variables and a manual signal provided by the user is used to handle the activation/deactivation of the detection module. The proposed oncoming traffic detection module computes spatiotemporal images from a set of pre-defined scan-lines which are related to the position of the road. A novel spatio-temporal motion descriptor is proposed (STHOL) accounting the number of lines, their orientation and length of the spatio-temporal images. A Bayesian framework is used to trigger the warning signal using multivariate Normal Density Functions. Experiments are conducted on image data captured from a vehicle parked at different locations of an urban environment, including different lighting conditions. We demonstrate that the proposed approach provides robust results maintaining processing rates close to real-time.
D. F. Llorca - One of the best experts on this subject based on the ideXlab platform.
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Vision-based parking assistance system for leaving perpendicular and angle parking lots
2013 IEEE Intelligent Vehicles Symposium (IV), 2013Co-Authors: D. F. Llorca, S. Álvarez, M. A. SoteloAbstract:Backing-out maneuvers in perpendicular or angle parking lots are one of the most dangerous maneuvers, specially in cases where side parked cars block the driver view of the potential traffic flow. In this paper a new vision-based Advanced Driver Assistance System (ADAS) is proposed to automatically warn the driver in such scenarios. A monocular gray-scale camera is installed at the back-right side of the vehicle. A Finite State Machine (FSM) defined according to three CAN-Bus variables and a manual signal provided by the user is used to handle the activation/deactivation of the detection module. The proposed oncoming traffic detection module computes spatiotemporal images from a set of pre-defined scan-lines which are related to the position of the road. A novel spatio-temporal motion descriptor is proposed (STHOL) accounting the number of lines, their orientation and length of the spatio-temporal images. A Bayesian framework is used to trigger the warning signal using multivariate Normal Density Functions. Experiments are conducted on image data captured from a vehicle parked at different locations of an urban environment, including different lighting conditions. We demonstrate that the proposed approach provides robust results maintaining processing rates close to real-time.
Anders Kallner - One of the best experts on this subject based on the ideXlab platform.
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further on creating Normal Density Functions in microsoft excel
Accreditation and Quality Assurance, 2016Co-Authors: Niklas Bark, Anders KallnerAbstract:Simulations play an increasing role in metrology and analytical chemistry, particularly the use of simulated Normal distributions. Microsoft Excel is available to almost everybody and Normal distributions can be simulated using either an innate function or other algorithms. We explore the success of five different algorithms to simulate Normal distributions and compare the outcome with a simulation coded in R. The Normality of 106 data points simulated by the chosen algorithms was tested by different recognized statistical procedures and Q–Q plots. They all failed the statistical procedures, but evaluating the Q–Q plots revealed different types of deviations. It also showed that the deviations, although statistically significant, most likely do not have any practical relevance in laboratory work.
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Further on creating Normal Density Functions in Microsoft ® Excel
Accreditation and Quality Assurance, 2016Co-Authors: Niklas Bark, Anders KallnerAbstract:Simulations play an increasing role in metrology and analytical chemistry, particularly the use of simulated Normal distributions. Microsoft Excel is available to almost everybody and Normal distributions can be simulated using either an innate function or other algorithms. We explore the success of five different algorithms to simulate Normal distributions and compare the outcome with a simulation coded in R. The Normality of 106 data points simulated by the chosen algorithms was tested by different recognized statistical procedures and Q–Q plots. They all failed the statistical procedures, but evaluating the Q–Q plots revealed different types of deviations. It also showed that the deviations, although statistically significant, most likely do not have any practical relevance in laboratory work.
S. Álvarez - One of the best experts on this subject based on the ideXlab platform.
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Vision-based parking assistance system for leaving perpendicular and angle parking lots
2013 IEEE Intelligent Vehicles Symposium (IV), 2013Co-Authors: D. F. Llorca, S. Álvarez, M. A. SoteloAbstract:Backing-out maneuvers in perpendicular or angle parking lots are one of the most dangerous maneuvers, specially in cases where side parked cars block the driver view of the potential traffic flow. In this paper a new vision-based Advanced Driver Assistance System (ADAS) is proposed to automatically warn the driver in such scenarios. A monocular gray-scale camera is installed at the back-right side of the vehicle. A Finite State Machine (FSM) defined according to three CAN-Bus variables and a manual signal provided by the user is used to handle the activation/deactivation of the detection module. The proposed oncoming traffic detection module computes spatiotemporal images from a set of pre-defined scan-lines which are related to the position of the road. A novel spatio-temporal motion descriptor is proposed (STHOL) accounting the number of lines, their orientation and length of the spatio-temporal images. A Bayesian framework is used to trigger the warning signal using multivariate Normal Density Functions. Experiments are conducted on image data captured from a vehicle parked at different locations of an urban environment, including different lighting conditions. We demonstrate that the proposed approach provides robust results maintaining processing rates close to real-time.
Jay R. Walton - One of the best experts on this subject based on the ideXlab platform.
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An application of linear feature selection to estimation of proportions
Communications in Statistics-theory and Methods, 2007Co-Authors: L. F. Guseman, Jay R. WaltonAbstract:Let X be a random n-vector whose Density function is given by a mixture of known multivariate Normal Density Functions where the corresponding mixture proportions (a priori probabilities) are unknown. We present a numerically tractable method for obtaining estimates of the mixture proportions based on the linear feature selection technique of Guseman, Peters and Walker (1975).
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Methods for estimating proportions of convex combinations of Normals using linear feature selection
Communications in Statistics-theory and Methods, 2007Co-Authors: L. F. Guseman, Jay R. WaltonAbstract:Let X be a random n-vector whose Density function is given by a mixtur.e of two Density Functions, h1 and h2 with unknown mixture proportions, Y1 and Y2 We assume that each of h1 and h2 is a convex combination of known multivariate Normal Density Functions whose corresponding mixture proportions are also unknown. We present three numerically tractable methods for estimating Y1 and Y2 related to the technique of Guseman and Walton (1977), and based on the linear feature selection technique of Guseman, Peters and Walker (1975).
