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检索条件"机构=Computer Vision Research Group in the Institute of Informatics"

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Improving Clustering Algorithms for Image Segmentation using Contour and Region Information

Improving Clustering Algorithms for Image Segmentation using...

引用

IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR

作者： Arnau Oliver Xavier Munoz Joan Batlle Lluis Pacheco Jordi Freixenet Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Spain

In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach

关键词： Clustering algorithms Image segmentation Partitioning algorithms Proposals Clustering methods computer vision Robot kinematics Robot vision systems informatics Application software

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Augmented state Kalman filtering for AUV navigation

Augmented state Kalman filtering for AUV navigation

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IEEE International Conference on Robotics and Automation (ICRA)

作者： R. Garcia J. Puig P. Ridao X. Cufi Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Spain

Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle position.

关键词： Kalman filters Filtering Navigation Motion estimation Underwater vehicles Oceans Remotely operated vehicles Cameras Sea floor State estimation

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Cheaper Pre-training Lunch: An Efficient Paradigm for Object Detection 1

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16th European Conference on computer vision, ECCV 2020

作者： Zhou, Dongzhan Zhou, Xinchi Zhang, Hongwen Yi, Shuai Ouyang, Wanli The University of Sydney SenseTime Computer Vision Research Group Sydney Australia Institute of Automation Chinese Academy of Sciences and University of Chinese Academy of Sciences Beijing China Sensetime Research Hong Kong

ISBN: (数字)9783030585983

ISBN: (纸本)9783030585976

In this paper, we propose a general and efficient pre-training paradigm, Montage pre-training, for object detection. Montage pre-training needs only the target detection dataset while taking only 1/4 computational resources compared to the widely adopted ImageNet pre-training. To build such an efficient paradigm, we reduce the potential redundancy by carefully extracting useful samples from the original images, assembling samples in a Montage manner as input, and using an ERF-adaptive dense classification strategy for model pre-training. These designs include not only a new input pattern to improve the spatial utilization but also a novel learning objective to expand the effective receptive field of the pre-trained model. The efficiency and effectiveness of Montage pre-training are validated by extensive experiments on the MS-COCO dataset, where the results indicate that the models using Montage pre-training are able to achieve on-par or even better detection performances compared with the ImageNet pre-training. © 2020, Springer Nature Switzerland AG.

关键词： Deep neural networks

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A system to evaluate the accuracy of a visual mosaicking methodology

A system to evaluate the accuracy of a visual mosaicking met...

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OCEANS

作者： R. Garcia J. Batlle X. Cufi Institute of Informatics and Applications Computer Vision and Robotics Group University of Girona Girona Spain

When underwater vehicles navigate close to the ocean floor, computer vision techniques can be applied to obtain motion estimates. A complete system to create visual mosaics of the seabed is described in this paper. Unfortunately, the accuracy of the constructed mosaic is difficult to evaluate. The use of a laboratory setup to obtain an accurate error measurement is proposed. The system consists on a robot arm carrying a downward looking camera. A pattern formed by a white background and a matrix of black dots uniformly distributed along the surveyed scene is used to find the exact image registration parameters. When the robot executes a trajectory (simulating the motion of a submersible), an image sequence is acquired by the camera. The estimated motion computed from the encoders of the robot is refined by detecting, to subpixel accuracy, the black dots of the image sequence, and computing the 2D projective transform which relates two consecutive images. The pattern is then substituted by a poster of the sea floor and the trajectory is executed again, acquiring the image sequence used to test the accuracy of the mosaicking system.

关键词： Image sequences Underwater vehicles Motion estimation Robot vision systems Cameras Navigation Oceans computer vision Laboratories computer errors

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Estimating the motion of an underwater robot from a monocular image sequence

Estimating the motion of an underwater robot from a monocula...

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： R. Garcia X. Cufi M. Carreras Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Spain

When underwater vehicles perform navigation close to the ocean floor, computer vision techniques can be applied to obtain quite accurate motion estimates. The most crucial step in the vision-based estimation of the vehicle motion consists on detecting matchings between image pairs. Here we propose the extensive use of texture analysis as a tool to ameliorate the correspondence problem in underwater images. Once a robust set of correspondences has been found, the three-dimensional motion of the vehicle can be computed with respect to the bed of the sea. Finally, motion estimates allow the construction of a map that could aid to the navigation of the robot.

关键词： Motion estimation Robots Navigation Underwater vehicles Oceans Floors computer vision Motion detection Vehicle detection Image analysis

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Use of decision trees in colour feature selection. Application to object recognition in outdoor scenes

Use of decision trees in colour feature selection. Applicati...

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IEEE International Conference on Image Processing

作者： J. Freixenet X. Llado J. Marti X. Cufi Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Catalonia Spain

A new method for the automated selection of colour features is described. The algorithm consists of two stages of processing. In the first, a complete set of colour features is calculated for every object of interest in an image. In the second stage, each object is mapped into several n-dimensional feature spaces in order to select the feature set with the smallest variables able to discriminate the remaining objects. The evaluation of the discrimination power for each concrete subset of features is performed by means of decision trees composed of linear discrimination functions. This method can provide valuable help in outdoor scene analysis where no colour space has been demonstrated as being the most suitable. Experiment results recognizing objects in outdoor scenes are reported.

关键词： Decision trees Object recognition Layout Application software Geometry computer vision Robot vision systems Robotics and automation informatics Concrete

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Understanding the learners' actions when using mathematics learning tools

Understanding the learners' actions when using mathematics l...

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Int. Conf. on Artificial Intelligence and Symbolic Computation, AISC 2012, Symp. on the Integration of Symbolic Computation and Mechanized Reasoning, Calculemus 2012, DML 2012, Conf. on Mathematical Knowledge Management, MKM 2012, Part of CICM 2012

作者： Libbrecht, Paul Rebholz, Sandra Herding, Daniel Müller, Wolfgang Tscheulin, Felix Institute for Mathematics and Informatics Karlsruhe University of Education Germany Media Education and Visualization Group Weingarten University of Education Germany Computer-Supported Learning Research Group RWTH Aachen University Germany

ISBN: (纸本)9783642313738

The use of computer-based mathematics tools is widespread in learning. Depending on the way that these tools assess the learner's solution paths, one can distinguish between automatic assessment tools and semi-automatic assessment tools. Automatic assessment tools directly provide all feedback necessary to the learners, while semi-automatic assessment tools involve the teachers as part the assessment process. They are provided with as much information as possible on the learners' interactions with the tool. How can the teachers know how the learning tools were used and which intermediate steps led to a solution? How can the teachers respond to a learner's question that arises while using a computer tool? Little is available to answer this beyond interacting directly with the computer and performing a few manipulations to understand the tools' state. This paper presents SMALA, a web-based logging architecture that addresses these problems by recording, analyzing and representing user actions. While respecting the learner's privacy, the SMALA architecture supports the teachers by offering fine-grained representations of the learners' activities as well as overviews of the progress of a classroom. © 2012 Springer-Verlag.

关键词： Teaching

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Towards a real-time vision-based navigation system for a small-class UUV

Towards a real-time vision-based navigation system for a sma...

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： R. Garcia T. Nicosevici P. Ridao D. Ribas Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Spain

This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory.

关键词： Real time systems Motion estimation Underwater vehicles Sea measurements Position measurement Dead reckoning Sonar navigation Robot vision systems Hydrodynamics Costs

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Omnidirectional depth computation from a single image

Omnidirectional depth computation from a single image

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2005 IEEE International Conference on Robotics and Automation

作者： Orghidan, Radu Mouaddib, El Mustapha Salvi, Joaquim Centre de Robotique Electrotechnique et d'Automatique Université de Picardie Jules Verne Amiens France Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Catalonia Spain

ISBN: (纸本)078038914X

Omnidirectional cameras offer a much wider field of view than the perspective ones and alleviate the problems due to occlusions. However, both types of cameras suffer from the lack of depth perception. A practical method for obtaining depth in computer vision is to project a known structured light pattern on the scene avoiding the problems and costs involved by stereo vision. This paper is focused on the idea of combining omnidirectional vision and structured light with the aim to provide 3D information about the scene. The resulting sensor is formed by a single catadioptric camera and an omnidirectional light projector. It is also discussed how this sensor can be used in robot navigation applications. © 2005 IEEE.

关键词： Cameras

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A NOVEL BULK DATA TRANSFER MECHANISM ON PARTIAL REPLICA

A NOVEL BULK DATA TRANSFER MECHANISM ON PARTIAL REPLICA

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IEEE International Conference on Communications Technology and Applications

作者： Zhang, Chen Gao, Peng Liu, Tao Chen, Yanming Welzl, Michael Chen, Tao Research Lab. China Mobile Group Design Institute China Department of Informatics University of Oslo Norway Computer Network Information Center Graduate University of CAS Beijing China

ISBN: (纸本)9781424448203

We introduce a "Bulk Data Transfer" (BDT) mechanism across multi-Autonomous System (AS). The mechanism performance is limited by the positions of source or replica servers and by the inter/intra AS routing strategies. Therefore, a new mechanism is proposed to enable the source peer to create several virtual replica servers to transfer the data to the destination peer together. The mechanism works on the Peer-to-Peer (P2P) layer and can adapt to the changes of the lower networks. Evaluations by simulation and in a real network proved that the proposed mechanism can enhance the transfer performance and reliability.

关键词： Bulk Data Transfer Replica Management Grid Network Next Generation Network

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