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IEEE International Conference on Image Processing

作者： R. Garcia C. Xevi J. Battle Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Spain Computer Vision and Robotics Group E.P.S. Girona Spain Universitat de Girona Girona Catalunya ES

This paper presents an approach to ameliorate the reliability of the correspondence points relating two consecutive images of a sequence. The images are especially difficult to handle, since they have been acquired by a camera looking at the sea floor while carried by an underwater robot. Underwater images are usually difficult to process due to light absorption, changing image radiance and lack of well-defined features. A new approach based on gray-level region matching and selective texture analysis significantly improves the matching reliability.

关键词： Underwater tracking Image analysis Image sequence analysis Image texture analysis Robot vision systems Cameras Motion detection Vehicle detection Underwater vehicles Testing

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Explicit Model Predictive Control Design based on Constrained Zonotope Propagation

Explicit Model Predictive Control Design based on Constraine...

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School on Dynamics of Complex Networks and their Application in Intellectual robotics (DCNAIR)

作者： Ali Jnadi Ramil Khusainov Simeon Nedelchev Sergei Savin Institute of Robotics and Computer Vision Innopolis University Innopolis Russia Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

Zonotopes have become a widely used tool in control design, demonstrating their effectiveness in various applications ranging from state estimation to explicit model predictive control. However, the traditional use of zonotopes is limited by a set certain geometric shapes that restrict the range of state sets that can be considered. This paper proposes a novel approach to control design using constrained zonotopes that can encode arbitrary polytopes. We present a propagation scheme and an affine approximation of the exact control law for this representation, and discuss issues related to center identification for constrained zonotopes. A fast method for detecting set membership is also proposed based on lifting the constrained zonotopes into a higher dimensional space. The proposed method extends the range of shapes that can be considered in control design and offers a promising alternative to the limitations of regular zonotopes. It has the potential for wide-ranging impact in various areas of control, providing a valuable tool for solving complex control problems.

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ROV-Aided Dam Inspection: Practical Results

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IFAC Proceedings Volumes 2003年第21期36卷 271-274页

作者： Joan Batlle Tudor Nicosevici Rafael Garcia Marc Carreras Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona E.P.S. 17071 Girona Spain

Nowadays Unmanned Underwater Vehicles (UUVs) are used in a growing number of underwater missions, mostly inspections of different types of installations such as: telecommunication cables, pipes or oil extraction installations. A field where UUVs are still starting to prove their utility is dam inspection. This paper presents details our first approach in dam inspection. A set of experiments carried out at a dam in Romania is described. Advantages and drawbacks of using a small-class underwater vehicle are analyzed for this type of missions.

关键词： computer vision teleoperation fault detection motion estimation

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On the Spacetime Geometry of Galilean Cameras

On the Spacetime Geometry of Galilean Cameras

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Conference on computer vision and Pattern Recognition (CVPR)

作者： Yaser Sheikh Alexei Gritai Mubarak Shah Robotics Institute Carnegie Mellon University USA Computer Vision Laboratory University of Central Florida USA

In this paper, a projection model is presented for cameras moving at constant velocity (which we refer to as Galilean cameras). To that end, we introduce the concept of spacetime projection and show that perspective imaging and linear pushbroom imaging are specializations of the proposed model. The epipolar geometry between two such cameras is developed and we derive the Galilean fundamental matrix. We show how six different "fundamental" matrices can be directly recovered from the Galilean fundamental matrix including the classic fundamental matrix, the linear pushbroom (LP) fundamental matrix and a fundamental matrix relating epipolar plane images (EPIs). To estimate the parameters of this fundamental matrix and the mapping between videos in the case of planar scenes we describe linear algorithms and report experimental performance of these algorithms.

关键词： Cameras Transmission line matrix methods Videos Robot vision systems Layout computer vision Laboratories Parameter estimation Computational geometry Orbital robotics

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Robotic workcell for sole grasping in footwear manufacturing

Robotic workcell for sole grasping in footwear manufacturing

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Guillermo Oliver Pablo Gil Fernando Torres Automatics Robotics and Artificial Vision Lab (AUROVA). Computer Science Research Institute University of Alicante Spain

ISBN: (数字)9781728189567

ISBN: (纸本)9781728189574

The goal of this paper is to present a robotic workcell to automate several tasks of the cementing process in footwear manufacturing. Our cell's main applications are sole digitization of a wide variety of footwear, glue dispensing and sole grasping from conveyor belts. This cell is made up of a manipulator arm endowed with a gripper, a conveyor belt and a 3D scanner. We have integrated all the elements into a ROS simulation environment facilitating control and communication among them, also providing flexibility to support future extensions. We propose a novel method to grasp soles of different shape, size and material, exploiting the particular characteristics of these objects. Our method relies on object contour extraction using concave hulls. We evaluate it on point clouds of 16 digitized real soles in three different scenarios: concave hull, k-NNs extension and PCA correction. While we have tested this workcell in a simulated environment, the presented system's performance is scheduled to be tested on a real setup at INESCOP facilities in the upcoming months.

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Online 3D Underwater Exploration and Coverage

Online 3D Underwater Exploration and Coverage

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Symposium on Autonomous Underwater Vehicle Technology (AUV)

作者： Eduard Vidal Narcís Palomeras Marc Carreras Computer Vision and Robotics Institute Universitat de Girona Pic de Peguera 13 Girona Spain

ISBN: (纸本)9781728102542

This work proposes a novel 3-dimensional (3D) exploration and coverage methodology for autonomous underwater vehicles (AUVs). Exploration can be defined as the task of discovering an unknown region in the space. Most robotic exploration algorithms seek full coverage of the unknown region with data from one sensor (in the underwater domain, it is usually occupancy data from profiling sonars, or optical data from cameras). Our method is able to guide the robot so that full discovery and coverage is obtained in a single exploration for both occupancy data and optical data. Since the algorithm has to run in the AUV's onboard computer, with limited processing power, our method is based around efficient operations that can be performed to an octree data structure. This work extends our previous 2-dimensional (2D) method, which has proved to work in real tests conducted with the Sparus II AUV. In this work, we have used three real datasets to generate environments for its exploration in simulation: an underwater seamount, a shipwreck and an underwater cave. Results using the Girona 500 AUV show the feasibility of our exploration approach in all tested scenarios.

关键词： Cameras Three-dimensional displays Robot vision systems Optical sensors Optical imaging

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EARLY ORIENTATION SELECTION—INFERRING TRACE, TANGENT, AND CURVATURE FIELDS

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International Journal of Pattern Recognition and Artificial Intelligence 1988年第3期2卷 443-457页

作者： STEVEN W. ZUCKER Canadian Institute for Advanced Research Computer Vision and Robotics Laboratory Department of Electrical Engineering McGill University Montréal Québec Canada

Orientation selection is the inference of orientation information out of images. It is one of the foundations on which other visual structures are built, since it must precede the formation of contours out of pointillist data and surfaces out of surface markings. We take a differential geometric view in defining orientation selection and develop algorithms for actually doing it. The goal of these algorithms is formulated in mathematical terms as the inference of a vector field of tangents (to the contours), and the algorithms are studied in both abstract and computational forms. They are formulated as matching problems, and algorithms for solving them are reduced to biologically plausible terms. We show that two different matching problems are necessary, the first for 1-dimensional contours (which we refer to as Type I processes) and the second for 2-dimensional flows (or Type II processes).

关键词： computer vision Orientation selection Curve detection Relaxation Edge detection Texture

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On the Direct Estimation of the Fundamental Matrix

On the Direct Estimation of the Fundamental Matrix

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Conference on computer vision and Pattern Recognition (CVPR)

作者： Yaser Sheikh Asaad Hakeem Mubarak Shah Robotics Institute Carnegie Mellon University USA Computer Vision Laboratory University of Central Florida USA

The fundamental matrix is a central construct in the analysis of images captured from a pair of cameras and many feature-based methods have been proposed for its computation. In this paper, we propose a direct method for estimating the fundamental matrix where the motion between the frames is small (e.g. between successive frames of a video). To achieve this, a warping function is presented for the fundamental matrix by using the brightness constancy constraint in conjunction with geometric constraints. Using this warping function, an iterative hierarchical algorithm is described to recover accurate estimates of the fundamental matrix. We present results of experimentation to evaluate the performance of the proposed approach and demonstrate improved accuracy in the computation of the fundamental matrix.

关键词： Transmission line matrix methods Motion estimation computer vision Cameras Iterative algorithms Iterative methods Robot vision systems Laboratories Image analysis Brightness

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Model-based Guidance, Navigation and Control architecture for an Autonomous Underwater Vehicle

Model-based Guidance, Navigation and Control architecture fo...

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OCEANS

作者： Jose Villa Guillem Vallicrosa Jussi Aaltonen Pere Ridao Kari T. Koskinen Tampere University Tampere Finland Computer Vision and Robotics Institute Universitat de Girona Girona Spain

ISBN: (数字)9781728154466

ISBN: (纸本)9781728184098

This article studies the design, modeling, and implementation of a model-based Guidance, Navigation, and Control (GNC) architecture for an Autonomous Underwater Vehicle (AUV). First, effective simulation modeling is developed using a theoretical six-degree-of-freedom (6DoF) dynamic model. Then, this study considers two GNC algorithms (simple and advanced). The simple GNC algorithm considers three different kinds of PID controllers (velocity, velocity-position, and position), and the advanced GNC algorithm enables path-following and data acquisition and processing from an underwater sensor. The path following is based on the position control using a unique PID controller and obtains its waypoints from a wall detection algorithm. This wall detection algorithm uses a mechanical imaging sonar as the main perception sensor. Finally, an implementation challenge in two control scenarios is addressed to validate the designed GNC architecture and to carry out model-verification of the position PID controller.

关键词： Autonomous underwater vehicles Heuristic algorithms Sonar Sonar navigation Detection algorithms Vehicle dynamics Sonar detection

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Towards Combating Frequency Simplicity-biased Learning for Domain Generalization 38

Towards Combating Frequency Simplicity-biased Learning for D...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： He, Xilin Hu, Jingyu Lin, Qinliang Luo, Cheng Xie, Weicheng Song, Siyang Khan, Muhammad Haris Shen, Linlin Computer Vision Institute School of Computer Science & Software Engineering Shenzhen University China Shenzhen Institute of Artificial Intelligence and Robotics for Society China Guangdong Provincial Key Laboratory of Intelligent Information Processing China University of Exeter United Kingdom Mohamed bin Zayed University of Artificial Intelligence United Arab Emirates

Domain generalization methods aim to learn transferable knowledge from source domains that can generalize well to unseen target domains. Recent studies show that neural networks frequently suffer from a simplicity-biased learning behavior which leads to over-reliance on specific frequency sets, namely as frequency shortcuts, instead of semantic information, resulting in poor generalization performance. Despite previous data augmentation techniques successfully enhancing generalization performances, they intend to apply more frequency shortcuts, thereby causing hallucinations of generalization improvement. In this paper, we aim to prevent such learning behavior of applying frequency shortcuts from a data-driven perspective. Given the theoretical justification of models' biased learning behavior on different spatial frequency components, which is based on the dataset frequency properties, we argue that the learning behavior on various frequency components could be manipulated by changing the dataset statistical structure in the Fourier domain. Intuitively, as frequency shortcuts are hidden in the dominant and highly dependent frequencies of dataset structure, dynamically perturbating the over-reliance frequency components could prevent the application of frequency shortcuts. To this end, we propose two effective data augmentation modules designed to collaboratively and adaptively adjust the frequency characteristic of the dataset, aiming to dynamically influence the learning behavior of the model and ultimately serving as a strategy to mitigate shortcut learning. Code is available at AdvFrequency. © 2024 Neural information processing systems foundation. All rights reserved.

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