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11
Evaluation of Road Marking Feature Extraction
- ITSC 2008. 11th International IEEE Conference on
, 2008
"... All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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Cited by 29 (2 self)
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All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.
Backward Segmentation and Region Fitting for Geometrical Visibility Range Estimation
"... Abstract. We present a new application of computer vision: continuous measurement of the geometrical visibility range on inter-urban roads, solely based on a monocular image acquisition system. To tackle this problem, we propose first a road segmentation scheme based on a Parzenwindowing of a color ..."
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Cited by 5 (1 self)
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Abstract. We present a new application of computer vision: continuous measurement of the geometrical visibility range on inter-urban roads, solely based on a monocular image acquisition system. To tackle this problem, we propose first a road segmentation scheme based on a Parzenwindowing of a color feature space with an original update that allows us to cope with heterogeneously paved-roads, shadows and reflections, observed under various and changing lighting conditions. Second, we address the under-constrained problem of retrieving the depth information along the road based on the flat word assumption. This is performed by a new region-fitting iterative least squares algorithm, derived from half-quadratic theory, able to cope with vanishing-point estimation, and allowing us to estimate the geometrical visibility range. 1
Perceptible Level Lines and Isoperimetric Ratio
- In Int. Conf. on Image Processing
, 2000
"... This paper introduces a simple criterion to select the most important level lines from the numerous set obtained with a topographic map. A topographic map gives a morphological and a geometrical representation of the information contained in natural images. Most of level lines are perceptually negli ..."
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Cited by 4 (1 self)
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This paper introduces a simple criterion to select the most important level lines from the numerous set obtained with a topographic map. A topographic map gives a morphological and a geometrical representation of the information contained in natural images. Most of level lines are perceptually negligible and may be removed without noticeable distortion. Such curves, which do not carry information on the shape of the objects, are oscillating very quickly. They can be discriminated from the others by means of the isoperimetric ratio of the region they delimit. The main advantage of the isoperimetric criterion lies in its invariance with respect to contrast changes. As a result of, the topographic map of the remaining level lines achieves a segmentation of the image with most borders matching the perceptual edges. This segmentation being invariant under changes of contrast is a great alternative to classical segmentation or edge detection methods, when to be used to compare the content of...
Concatenate feature extraction for robust 3d elliptic object localization. Applied Computing 2004
- Proceedings of the 2004 ACM Symposium on Applied Computing
, 2004
"... Developing an efficient object localization system for complicated industrial objects is an important, yet difficult robotic task. To tackle this problem, we have developed a system consisting first of a vision model acquisition editor, where the object salient features are acquired through a human- ..."
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Cited by 4 (2 self)
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Developing an efficient object localization system for complicated industrial objects is an important, yet difficult robotic task. To tackle this problem, we have developed a system consisting first of a vision model acquisition editor, where the object salient features are acquired through a human-in-the-loop approach. Subsequently, two feature extraction algorithms, region-growing and edge-grouping, are applied to the object scene. Finally, by Kalman filter estimation of a proper ellipse representation, our object localization system successfully generates ellipse hypotheses by grouping edge fragments in the scene. The proposed system is validated by experiments using actual industrial objects.
Topographic Maps of Color Images
, 2000
"... We address the problem of extending topographic maps to color images. A topographic map gives a morphological and a geometrical representation of the information contained in natural images. Two approaches are presented and discussed. The first one is new and consists in defining a total order in IR ..."
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Cited by 3 (0 self)
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We address the problem of extending topographic maps to color images. A topographic map gives a morphological and a geometrical representation of the information contained in natural images. Two approaches are presented and discussed. The first one is new and consists in defining a total order in IR in accordance with the human visual perception of shapes. This allows to define color topographic maps in the same way that what it has been done for graylevel topographic maps. It has the advantage of leading all properties known in the gray-level case to remain true in the color case. But the map contains a so huge quantity of data that it has to be drastically simplified. The second approach, based on a so far unpublished result [4], allows to build a simplified representation by using the geometry given by the luminance component only. We present experiments which illustrate the advantages and the drawbacks of each method.
An improved linearparabolic model for lane following and curve detection
- in Proceedings of SIBGRAPI
, 2005
"... In this paper, we propose a new model for lane tracking and curve detection. We use a linear-parabolic model for each lane boundary, and apply constraints to link both lane boundaries based on the expected geometry of the road. The parabolic part of the model, which fits the far field, is then used ..."
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Cited by 2 (1 self)
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In this paper, we propose a new model for lane tracking and curve detection. We use a linear-parabolic model for each lane boundary, and apply constraints to link both lane boundaries based on the expected geometry of the road. The parabolic part of the model, which fits the far field, is then used to analyze the geometry of the road ahead (straight, right curve or left curve), with applications in driver’s as-sistance systems and road inspection. Experimental re-sults indicate that introduced geometric constraints result in a more consistent fit if compared to the individual fitting of each lane boundary, and that the parabolic part of the model can be effectively used to keep the driver informed about the geometry of the road in front of him/her. 1
assembly
, 2005
"... Salient feature extraction of industrial objects for an automated ..."
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A New Edge-Grouping Algorithm for Multiple Complex Objects Localization
"... Abstract. We present a new algorithm that provides an efficient localization method of elliptic industrial objects. Our proposed feature extraction inherits edge grouping approaches. But instead of utilizing edge linkage to restore incomplete contours, we introduce criteria of feature's paramet ..."
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Abstract. We present a new algorithm that provides an efficient localization method of elliptic industrial objects. Our proposed feature extraction inherits edge grouping approaches. But instead of utilizing edge linkage to restore incomplete contours, we introduce criteria of feature's parameters and optimize the criteria using an extended Kalman filter. Through a new parameter estimation under a proper ellipse representation, our system successfully generates ellipse hypotheses by grouping the fragmental edges in the scene. An important advantage of using our Kalman filter approach is that a desired feature can be robustly extracted regardless of ill-condition of partial edges and outlier noises. The experiment results demonstrate a robust localization performance. 1
2004 ACM Symposium on Applied Computing Concatenate Feature Extraction for Robust 3D Elliptic Object Localization
"... Developing an efficient object localization system for complicated industrial objects is an important, yet difficult robotic task. To tackle this problem, we have developed a system consisting first of a vision model acquisition editor, where the object salient features are acquired through a human- ..."
Abstract
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Developing an efficient object localization system for complicated industrial objects is an important, yet difficult robotic task. To tackle this problem, we have developed a system consisting first of a vision model acquisition editor, where the object salient features are acquired through a human-in-the-loop approach. Subsequently, two feature extraction algorithms, region-growing and edge-grouping, are applied to the object scene. Finally, by Kalman filter estimation of a proper ellipse representation, our object localization system successfully generates ellipse hypotheses by grouping edge fragments in the scene. The proposed system is validated by experiments using actual industrial objects.
Project Data Project Group: Group 925
"... This project deals with the development of a computer vision system for handling an instance of the bin picking problem. The system performs pose estimation of randomly organised stator housings containing circular features with a known CAD model. The implemented system obtains 3-D information throu ..."
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This project deals with the development of a computer vision system for handling an instance of the bin picking problem. The system performs pose estimation of randomly organised stator housings containing circular features with a known CAD model. The implemented system obtains 3-D information through a binocular stereo setup. The individual stereo images are processed by a Canny edge detector followed by an edge segmentation and a least squares ellipse detection. The detected ellipses in each image are subject to a monocular pose estimation technique estimating two possible circular pose candidates for each ellipse. The correct pose candidates are determined by performing a matching between the circle pose candidates in each stereo image. The matching is done via an association graph search locating the maximally weighted clique through the use of simulated annealing. The final pose candidates are verified by back projection in a distance transformed edge image. System tests justified the choice of the circular feature due to the presence of detectable stator housings per bin configuration. Tests on simulated data showed acceptable error measures both for position and orientation estimation. The final conclusion was that the implemented method could form a useful part, handling certain pose situations, in a final bin picking system.
