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4th International conference on computer vision theory and Applications

作者： Posada, Luis-Felipe Nierobisch, thomas Hoffmann, Frank Bertram, Torsten Tech Univ Dortmund Chair Control Syst Engn Dortmund Germany

ISBN: (纸本)9789898111692

this paper proposes a novel framework for vision based door traversal that contributes to the ultimate goal of purely vision based mobile robot navigation. the door detection, door tracking and door traversal is accomplished by processing onmidirectional images. In door detection candidate line segments detected in the image are grouped and matched with prototypical door patterns. In door localisation and tracking a Kalman filter aggregates the visual information with the robots odometry. Door traversal is accomplished by a 2D visual servoing approach. the feasibility and robustness of the scheme are confirmed and validated in several robotic experiments in an office environment.

关键词： Omnidirectional vision Door passing robotic behaviour Visual navigation Door detection Visual servoing

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A Support Vector Machine Based Online Learning Approach for Automated Visual Inspection

A Support Vector Machine Based Online Learning Approach for ...

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6th canadian conference on computer and robot vision

作者： Sun, Jun Sun, Qiao Univ Calgary Dept Mech & Mfg Engn Calgary AB T2N 1N4 Canada

ISBN: (纸本)9781424442119

In manufacturing industry there is a need for an adaptable automated visual inspection (AVI) system that can be used for different inspection tasks under different operation condition without requiring excessive retuning or retraining. this paper proposes an adaptable AVI scheme using an efficient and effective online learning approach. the AVI scheme uses a novel inspection model that consists of the two sub-models for localization and verification. In the AVI scheme, the region localization module is implemented by using a template-matching technique to locate the subject to be inspected based on the localization sub-mode. the defect detection module is realized by using the representative features obtained from the feature extraction module and executing the verification sub-model built in the model training module. A support vector machine (SVM) based online learning algorithm is proposed for training and updating the verification sub-model. In the case studies, the adaptable A VI scheme demonstrated its promising performances with respect to the training efficiency and inspection accuracy. the expected outcome of this research will be beneficial to the manufacturing industry.

关键词： Feature extraction

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Using Multi-view Recognition and Meta-data Annotation to Guide a robot's Attention

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INTERNATIONAL JOURNAL OF robotICS RESEARCH 2009年第8期28卷 976-998页

作者： thomas, Alexander Ferrari, Vittorio Leibe, Bastian Tuytelaars, Tinne Van Gool, Luc ESAT PSI VISICS KU Leuven B-3001 Heverlee Belgium ETH Comp Vis Lab CH-8092 Zurich Switzerland Rhein Westfal TH Aachen UMIC Res Ctr D-52056 Aachen Germany

In the transition from industrial to service robotics, robots will have to deal with increasingly unpredictable and variable environments. We present a system that is able to recognize objects of a certain class in an image and to identify their parts for potential interactions. the method can recognize objects from arbitrary viewpoints and generalizes to instances that have never been observed during training, even if they are partially occluded and appear against cluttered backgrounds. Our approach builds on the implicit shape model of Leibe et al. We extend it to couple recognition to the provision of meta-data useful for a task and to the case of multiple viewpoints by integrating it with the dense multi-view correspondence finder of Ferrari et al. Meta-data can be part labels but also depth estimates, information on material types, or any other pixelwise annotation. We present experimental results on wheelchairs, cars, and motorbikes.

关键词： object class recognition computer vision

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SIMULATING DYNAMICAL SYSTEMS FOR EARLY vision

SIMULATING DYNAMICAL SYSTEMS FOR EARLY VISION

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4th International conference on computer vision theory and Applications

作者： Dellen, Babette Woergoetter, Florentin Max Planck Inst Dynam & Self Org Bernstein Ctr Computat Neurosci Bunsenstr 10 Gottingen Germany UPC CSIC Inst Robot & Informat Ind E-08028 Barcelona Spain Univ Gottingen Bernstein Ctr Computat Neurosci Gottingen Germany

ISBN: (纸本)9789898111692

We propose a novel algorithm for stereo matching using a dynamical systems approach. the stereo correspondence problem is first formulated as an energy minimization problem. From the energy function, we derive a system of differential equations describing the corresponding dynamical system of interacting elements, which we solve using numerical integration. Optimization is introduced by means of a damping term and a noise term, an idea similar to simulated annealing. the algorithm is tested on the Middlebury stereo benchmark.

关键词： Early vision Stereo matching Energy minimization Dynamical systems

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Environment Classification for Indoor/Outdoor robotic Mapping

Environment Classification for Indoor/Outdoor Robotic Mappin...

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6th canadian conference on computer and robot vision

作者： Collier, Jack Ramirez-Serrano, Alejandro Def R&D Canada Suffield Autonomous Intelligent Syst Sect POB 4000 Stn Main Medicine Hat AB T1A 8K6 Canada Univ Calgary Dept Mech & Mfg Engn Calgary AB T2N 1N4 Canada

ISBN: (纸本)9781424442119

We present a novel perception system for mapping of indoor/outdoor environments with an Unmanned Ground Vehicle (UGV). the system uses image classification techniques to determine the operational environment of the UGV (indoor or outdoor). Based on the classification results, the appropriate mapping system is then deployed. Image features are extracted from video imagery and used to train a classification function using supervised learning techniques. this classification function is then used to classify new imagery. A perception module observes the classification results and switches the UGV's perception system, according to current needs and available (reliable) data as the UGV transitions from indoors to outdoors or vice versa. A terrain map that exploits GPS and Inertial Measurement Unit (IMU) data is used when operating outdoors, while a 2D laser based Simultaneous Localization and Mapping (SLAM) technique is used when operating indoors. Globally consistent maps are generated by transforming the indoor map data into the global reference frame, a capability unique to this algorithm.

关键词： Indoor positioning systems

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A Generic Moment Invariants Based Supervised Learning Framework for Classification Using Partial Object Information

A Generic Moment Invariants Based Supervised Learning Framew...

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6th canadian conference on computer and robot vision

作者： Minhas, Rashid Mohammed, Abdul Adeel Wu, Q. M. Jonathan Univ Windsor Dept Elect Engn Windsor ON N9B 3P4 Canada

ISBN: (纸本)9781424442119

We present a novel classification scheme which uses partial object information that is selected adaptively using modified distance transform and represented as moment invariants (Hu moments) to compensate for scale, translation and rotational transformation(s). the moment invariants of different parts of an object are learned using AdaBoost algorithm [1]. the classifier obtained using the proposed scheme is able to handle changes in illumination, pose, and varying inter-class and intra-class attributes. Partial information based classification shows robustness against object articulations, clutters, and occlusions. the first contribution of our proposed method is an adaptive selection of partial object information using modified distance transform that attempts to extract contours along with its neighborhood information in the form of blocks. Secondly, our proposed method is invariant to scaling, translation and rotation, and reliably classifies occluded objects using fractional information. Our proposed method achieved better detection and classification rate compared to other state-of-the-art schemes.

关键词： Classification (of information)

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An Efficient and Fast Active Contour Model for Salient Object Detection

An Efficient and Fast Active Contour Model for Salient Objec...

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6th canadian conference on computer and robot vision

作者： Ksantini, Riadh Shariat, Farnaz Boufama, Boubakeur Univ Windsor Sch Comp Sci Windsor ON N9B 3P4 Canada

ISBN: (纸本)9781424442119

In this paper we investigate the polarity information to improve the active contour model proposed by Chunming et al. [12]. Unlike the traditional level set formulations, the variational level set formulation proposed by [12] forces the level set function to be close to a signed distance function, and therefore completely eliminates the need of the re-initialization procedure and speeds up the curve evolution. However;like the majority of classical active contour models, the model proposed by [12] relies on a gradient based stopping function, depending on the image gradient, to stop the curve evolution. Consequently, using gradient information for noisy and textured images, the evolving curve may pass through or stop far from the salient object boundaries. Moreover, in this case, the isotropic smoothing Gaussian has to be strong, which will smooth the edges too. For these reasons, we propose the use of a polarity based stopping function. In fact, comparatively to the gradient information, the polarity information accurately distinguishes the boundaries or edges of the salient objects. Hence, Combining the polarity information with the active contour model of [12] we obtain a fast and efficient active contour model for salient object detection. Experiments are performed on several images to show the advantage of the polarity based active contour.

关键词： Object recognition

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PROJECTION PEAK ANALYSIS FOR RAPID EYE LOCALIZATION

PROJECTION PEAK ANALYSIS FOR RAPID EYE LOCALIZATION

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4th International conference on computer vision theory and Applications

作者： Dai, Jingwen Liu, Dan Su, Jianbo Shanghai Jiao Tong Univ Res Ctr Intelligent Robot Shanghai 200240 Peoples R China

ISBN: (纸本)9789898111692

this paper presents a new method of projection peak analysis for rapid eye localization. First, the eye region is segmented from the face image by setting appropriate candidate window. then, a threshold is obtained by histogram analysis of the eye region image to binarize and segment the eyes out of the eye region. thus, a series of projection peak will be derived from vertical and horizontal gray projection curves on the binary image, which is used to confirm the positions of the eyes. the proposed eye-localization method does not need any a priori knowledge and training process. Experiments on three face databases show that this method is effective, accurate and rapid in eye localization, which is fit for real-time face recognition system.

关键词： Eye localization threshold Segmentation Projection peak

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CLASSIFIERS SENSITIVITY FOR BOUNDARY CASE TESTING SET IN thE FACE RECOGNITION ALGORIthM BASED ON thE ACTIVE SHAPE MODEL

CLASSIFIERS SENSITIVITY FOR BOUNDARY CASE TESTING SET IN THE...

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4th International conference on computer vision theory and Applications

作者： Florek, Andrzej Krol, Maciej Poznan Univ Tech Inst Control & Informat Engn Automat Control & Robot Div PL-60965 Poznan Poland

ISBN: (纸本)9789898111692

In this paper, experimental results from the face contour classification tests are shown. the presented approach is dedicated to a face recognition algorithm based on the Active Shape Model method. the results were obtained from experiments carried out on the set of 3300 images taken from 100 persons. Automatically fitted contours (as 194 ordered face contour points vector, where the contour consisted of eight components) were classified by Nearest Neighbourhood Classifier and Support Vector Machines classifier, after feature space decomposition, carried out by the Linear Discriminant Analysis method. Feature subspace size reduction and classification sensitivity analysis for boundary case testing set are presented.

关键词： Face recognition Active Shape Model Principal Component Analysis Linear Discriminant Analysis Support Vector Machine and Classification

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EAR SEGMETATION USING TOPOGRAPHIC LABELS

EAR SEGMETATION USING TOPOGRAPHIC LABELS

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4th International conference on computer vision theory and Applications

作者： Lankarany, Milad Ahmadyfard, Alireza Shahrood Univ Technol Dept Elect Engn & Robot Shahrood Iran

ISBN: (纸本)9789898111692

Ear segmentation is considered as the first step of all ear biometrics systems while the objective in separating the ear from its surrounding backgrounds is to improve the capability of automatic systems used for ear recognition. To meet this objective in the context of ear biometrics a new automatic algorithm based on topographic labels is presented here. the proposed algorithm contains four stages. First we extract topographic labels from the ear image. then using the map of regions for three topographic labels namely, ridge, convex hill and convex saddle hill we build a composed set of labels. the thresholding on this labelled image provides a connected component with the maximum number of pixels which represents the outer boundary of the ear. As well as addressing faster implementation and brightness insensitivity, the technique is also validated by performing completely successful ear segmentation tested on "USTB" database which contains 308 profile view images of the ear and its surrounding backgrounds.

关键词： Ear Biometrics Ear Segmentation Topographic Features

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