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17th International Conference on Informatics in Control, Automation and robotics, ICINCO 2020

作者： Peidró, Adrián Payá, Luis Cebollada, Sergio Román, Vicente Reinoso, Óscar Automation Robotics and Computer Vision Laboratory Miguel Hernández University Avda. de la Universidad s/n Elche03202 Spain

ISBN: (纸本)9783030924416

This paper presents a method to solve the forward kinematic problem of parallel robots, obtaining all real solutions. The method is illustrated with the 3UPS-PU parallel robot, and consists in eliminating one unknown to obtain an equation that constrains the admissible values of the remaining unknowns. This constraint defines a curve in the plane of the remaining unknowns, which contains all real solutions. The proposed method samples and scans this constraint curve in order to find all real solutions, using only analytical operations and k-dimensional trees. This method is able to find all real solutions and performs at least one order of magnitude faster than other numerical methods, while avoiding the complicated and lengthy symbolic expressions that traditional elimination procedures involve. The proposed method is also extended to the complex domain and another parallel robot (the 3RRR robot). © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Numerical methods

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Natural Scene Classification Inspired by Visual Perception and Cognition Mechanisms

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重庆理工大学学报（自然科学） 2011年第7期25卷 24-43页

作者： ZHANG Rui Robotics and Computer Vision Laboratory Dept. of Electrical and Computer Engineering Queen＇ s University Canada

The process of human natural scene categorization consists of two correlated stages: visual perception and visual cognition of natural *** by this fact,we propose a biologically plausible approach for natural scene image *** approach consists of one visual perception model and two visual cognition *** visual perception model,composed of two steps,is used to extract discriminative features from natural scene *** the first step,we mimic the oriented and bandpass properties of human primary visual cortex by a special complex wavelets transform,which can decompose a natural scene image into a series of 2D spatial structure *** the second step,a hybrid statistical feature extraction method is used to generate gist features from those 2D spatial structure *** we design a cognitive feedback model to realize adaptive optimization for the visual perception *** last,we build a multiple semantics based cognition model to imitate human cognitive mode in rapid natural scene *** on natural scene datasets show that the proposed method achieves high efficiency and accuracy for natural scene classification.

关键词： natural scene classification visual perception model visual cognition model

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Traffic Sign Detection With Event Cameras and DCNN 25

Traffic Sign Detection With Event Cameras and DCNN

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25th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2022

作者： Wzorek, Piotr Kryjak, Tomasz Embedded Vision Systems Group Agh University of Science and Technology Computer Vision Laboratory Department of Automatic Control and Robotics Kraków Poland Silesian University of Technology Department of Digital Systems Gliwice Poland

ISBN: (数字)9788362065424

ISBN: (纸本)9788362065424

In recent years, event cameras (DVS - Dynamic vision Sensors) have been used in vision systems as an alternative or supplement to traditional cameras. They are characterised by high dynamic range, high temporal resolution, low latency, and reliable performance in limited lighting conditions - parameters that are particularly important in the context of advanced driver assistance systems (ADAS) and self-driving cars. In this work, we test whether these rather novel sensors can be applied to the popular task of traffic sign detection. To this end, we analyse different representations of the event data: event frame, event frequency, and the exponentially decaying time surface, and apply video frame reconstruction using a deep neural network called FireNet. We use the deep convolutional neural network YOLOv4 as a detector. For particular representations, we obtain a detection accuracy in the range of 86.9-88.9% mAP@0.5. The use of a fusion of the considered representations allows us to obtain a detector with higher accuracy of 89.9% mAP@0.5. In comparison, the detector for the frames reconstructed with FireNet is characterised by an accuracy of 72.67% mAP@0.5. The results obtained illustrate the potential of event cameras in automotive applications, either as standalone sensors or in close cooperation with typical frame-based cameras. © 2022 Division of Signal Processing and Electronic Systems, Poznan University of Technology (DSPES PUT).

关键词： Cameras

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vision-based Lane Analysis: Exploration of Issues and Approaches for Embedded Realization

Vision-based Lane Analysis: Exploration of Issues and Approa...

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IEEE Conference on computer vision and Pattern Recognition Workshops

作者： R. K. Satzoda Mohan M. Trivedi Computer Vision and Robotics Research Laboratory University of California

ISBN: (纸本)9781479909940

Lane feature extraction is one of the key computational steps in lane analysis systems. In this paper, we propose a lane feature extraction method, which enables different configurations of embedded solutions that address both accuracy and embedded systems' constraints. The proposed lane feature extraction process is evaluated in detail using real world lane data, to explore its effectiveness for embedded realization and adaptability to varying contextual information like lane types and environmental conditions.

关键词： Lanes Feature extraction Extraction processes embedding

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Evolutionary Quasi-random Search for Hand Articulations Tracking

Evolutionary Quasi-random Search for Hand Articulations Trac...

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IEEE Conference on computer vision and Pattern Recognition

作者： Iason Oikonomidis Manolis I. A. Lourakis Antonis A. Argyros Computational Vision and Robotics Laboratory Institute of Computer Science

ISBN: (纸本)9781479951192

We present a new method for tracking the 3D position, global orientation and full articulation of human hands. Following recent advances in model-based, hypothesize-and-test methods, the high-dimensional parameter space of hand configurations is explored with a novel evolutionary optimization technique specifically tailored to the problem. The proposed method capitalizes on the fact that samples from quasi-random sequences such as the Sobol have low discrepancy and exhibit a more uniform coverage of the sampled space compared to random samples obtained from the uniform distribution. The method has been tested for the problems of tracking the articulation of a single hand (27D parameter space) and two hands (54D space). Extensive experiments have been carried out with synthetic and real data, in comparison with state of the art methods. The quantitative evaluation shows that for cases of limited computational resources, the new approach achieves a speed-up of four (single hand tracking) and eight (two hands tracking) without compromising tracking accuracy. Interestingly, the proposed method is preferable compared to the state of the art either in the case of limited computational resources or in the case of more complex (i.e., higher dimensional) problems, thus improving the applicability of the method in a number of application domains.

关键词： Computational modeling Optimization Kinematics Tracking Joints Accuracy Linear programming

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On the problem of determination of spring stiffness parameters for spring-mesh models

On the problem of determination of spring stiffness paramete...

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Medicine Meets Virtual Reality 16 - Parallel, Combinatorial, Convergent: NextMed by Design, MMVR 2008

作者： Quang Huy Viet, Huynh Hirai, Shinichi Shirai, Yoshiaki Yamaguchi, Satoshi Tanaka, Hiromi T. Kawasaki, Hiroshi Kawai, Yukiko Computer Vision and Graphics Laboratory Department of Information and Computer Science Saitama University Saitama Japan Laboratory for Integrated Machine Intelligence Department of Robotics Ritsumeikan University Kusatsu Japan Computer Vision Lab. Department of Human and Computer Intelligence Ritsumeikan University Kusatsu Japan Kawai Lab. Department of Computer Science Kyoto Sangyo University Kyoto Japan

ISBN: (纸本)9781586038229

On account of having real-time behavior and being easy to implement, spring meshes have been used for modeling deformable objects. Determining spring stiffness parameters for simulation of soft objects with high accuracy still remains a challenge. Allen Van Gelder derived an approximate formula for determining spring stiffness parameters based on strain analysis. Even though the experimental result showed the effectiveness, the method has not been investigated from a quantitative point of view. In this paper we propose a quantitative method for determining spring stiffness parameters. Moreover we propose a method to improve the accuracy by way of introducing torsional spring into the conventional spring mesh model. © 2008 The authors. All rights reserved.

关键词： Stiffness matrix

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Mobile beacon control algorithm that ensures observability in single range navigation

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IFAC-PapersOnLine 2016年第23期49卷 48-53页

作者： Mandi, Filip Mikovi, Nikola Palomeras, Narcís Carreras, Marc Vallicrosa, Guillem University of Zagreb Faculty of Electrical Engineering and Computing LABUST - Laboratory for Underwater Systems and Technologies Unska 3 Zagreb Croatia Computer Vision and Robotics Institute Universitat de Girona Parc Cientfic i Tecnolgic UdG Girona17003 Spain

Mobile beacon vehicles are used as navigational aid for autonomous underwater vehicles when performing navigation using single range measurements. They remove the constraints imposed on the underwater vehicle trajectory by executing trajectory that provides persistent range measurements. In this paper, control algorithm for beacon vehicle which ensures observability of the underwater vehicle's navigation filter is presented. It is characterized by small communication overhead, low computational complexity and it is deployable on both fully actuated and underactuated vehicles. The algorithm was tested in real-life environment and the acquired experimental results show that despite the presence of uncertainties and communication delays, the algorithm accomplishes its task. © 2016

关键词： Marine navigation Autonomous underwater vehicles Kalman filters Navigation Observability Autonomous Vehicles Communication delays Communication overheads Low computational complexity Marine systems Navigation filters Underactuated vehicles Underwater vehicles

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REAL-TIME MOTION DETECTION BASED ON DISCRETE COSINE TRANSFORM

REAL-TIME MOTION DETECTION BASED ON DISCRETE COSINE TRANSFOR...

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IEEE International Conference on Image Processing

作者： Tae-Hyun Oh Joon-Young Lee In So Kweon Robotics and Computer Vision Laboratory KAIST South Korea

We present a motion detection algorithm by a change detection filter matrix derived from Discrete Cosine Transform. Recently, a Fourier reconstruction scheme shows good results for motion detection. However, its computational cost is a major drawback. We revisit the problem and achieve two orders of magnitude faster than the previous algorithm with better performance. The proposed algorithm runs at about 800 frames per second for VGA resolution images on a consumer hardware by using only integer matrix multiplication and the symmetric property of the change detection filter matrix. In addition, our algorithm is fundamentally robust to sudden illumination changes because it works based on edge information. We verify our algorithm with challenging datasets that contain strong and sudden illumination changes.

关键词： Discrete cosine transforms Motion detection Lighting Vectors Change detection algorithms Robustness Algorithm design and analysis

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A biologically motivated approach to early visual computations: orientation selection, texture, and optical flow 4th

A biologically motivated approach to early visual computatio...

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4th International Conference on Pattern Recognition, 1988

作者： Zucker, Steven W. Computer Vision and Robotics Laboratory McGill Research Centre for Intelligent Machines McGill University MontréalQC Canada The Canadian Institute for Advanced Research Canada

ISBN: (纸本)9783540190363

The problem of curve detection decomposes naturally into two stages: (i) inferring the (discrete) trace and tangent to the curve;and (ii) finding integrals through the resultant tangent field. Orientation selection is the term used by physiologists for the first of these stages;i.e., for the process of extracting the tangents to piecewise smooth curves from a two-dimensional image. We present an analysis of the orientation selection process from a computational perspective that is strongly influenced by various biological constraints. As such, it provides both a solid foundation for curve detection algorithms within computer vision systems and illustrates the insights that can be gained by analyzing biological vision systems. Formal extensions to the algorithm can also be posed that provide further insight into texture and optical flow. © 1988, Springer-Verlag.

关键词： Optical flows

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Multimodal stereo image registration for pedestrian detection

Multimodal stereo image registration for pedestrian detectio...

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ITSC 2006: 2006 IEEE Intelligent Transportation Systems Conference

作者： Krotosky, Stephen Trivedi, Mohan Computer Vision and Robotics Research Laboratory University of California San Diego 9500 Gilman Dr. 0434 San Diego CA 92093 United States

ISBN: (纸本)1424400945

This paper presents an approach for the registration of multimodal imagery for pedestrian detection when the significant depth differences of objects in the scene precludes a global alignment assumption. Using maximization-of-mutual- information matching techniques and sliding correspondence windows over calibrated image pairs, we demonstrate successful registration of color and thermal data. We develop a robust method using disparity voting for determining the registration of each object in the scene and provide a statistically based measure for evaluating the match confidence. Testing shows successful registration in complex scenes with multiple people at different depths and levels of occlusion. © 2006 IEEE.

关键词： Image registration

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