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共 476 条记录，以下是281-290 订阅

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Towards embedded robot vision for multi-scale object recognition repeatability of interest points detected in half-octave binomial pyramids

Towards embedded robot vision for multi-scale object recogni...

引用

4th International conference on Pervasive and Embedded Computing and Communication Systems, PECCS 2014

作者： Entschev, Peter Andreas Neto, Hugo Vieira Graduate School of Electrical Engineering and Applied Computer Science Federal University of Technology Paranà Avenida Sete de Setembro 3165 Curitiba Brazil

ISBN: (纸本)9789897580000

the construction of multi-scale image pyramids is used in state-of-the-art methods that perform robust object recognition, such as SIFT and SURF. However, building such image pyramids is computationally expensive, especially when implementations in embedded systems with limited computing resources are considered. therefore, the use of alternative less expensive approaches are necessary if near real-time operation is desired. Previous work has reported that using binomial filters to construct half-octave multi-scale pyramids consumes only 1=4 of the processing time of the Gaussian pyramid originally used in the SIFT framework. Here we investigate how interest points detected using the binomial approach behave when compared to the Gaussian approach, focusing on repeatability. Experimental results show that in average up to 86% of interest points detected with the original SIFT pyramid building scheme are also detected when using the binomial method, despite of large gains in processing time. When rotation of image features is considered, experimental results demonstrate that slightly superior repeatability of interest points is achieved using the binomial pyramid.

关键词： Object recognition

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Pattern Recognition - 4th Mexican conference, MCPR 2012, Proceedings

Pattern Recognition - 4th Mexican Conference, MCPR 2012, Pro...

引用

4th Mexican conference on Pattern Recognition, MCPR 2012

ISBN: (纸本)9783642311482

the proceedings contain 34 papers. the topics discussed include: human sign recognition for robot manipulation;fuzzy sets for human fall pattern recognition;vision system for 3D reconstruction with telecentric lens;a tool for hand-sign recognition;improving the multiple alignments strategy for fingerprint verification;breaking reCAPTCHAs with unpredictable collapse: heuristic character segmentation and recognition;using short-range interactions and simulated genetic strategy to improve the protein contact map prediction;associative model for solving the wall-following problem;the list of clusters revisited;a heuristically perturbation of dataset to achieve a diverse ensemble of classifiers;compact and efficient permutations for proximity searching;and NURBS parameterization: a new method of parameterization using the correlation relationship between nodes.

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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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CRV 2018 Award Winners [4 awards]

CRV 2018 Award Winners [4 awards]

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canadian conference on computer and robot vision, CRV

the award winners and the titles of their award winning papers are listed.

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Quantifying the Impact of the Physical Setup of Stereo Camera Systems on Distance Estimations 4

Quantifying the Impact of the Physical Setup of Stereo Camer...

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4th IEEE International conference on robotic Computing (IEEE IRC)

作者： Golkowski, Alexander J. Handte, Marcus Roch, Peter Marron, Pedro J. Univ Duisburg Essen Networked Embedded Syst D-45127 Essen Germany

ISBN: (纸本)9781728152370

the ability to perceive the environment accurately is a core requirement for autonomous navigation. In the past, researchers and practitioners have explored a broad spectrum of sensors that can be used to detect obstacles or to recognize navigation targets. Due to their low hardware cost and high fidelity, stereo camera systems are often considered to be a particularly versatile sensing technology. Consequently, there has been a lot of work on integrating them into mobile robots. However, the existing literature focuses on presenting the concepts and algorithms used to implement the desired robot functions on top of a given camera setup. As a result, the rationale and impact of choosing this camera setup are usually neither discussed nor described. thus, when designing the stereo camera system for a mobile robot, there is not much general guidance beyond isolated setups that worked for a specific robot. To close the gap, this paper studies the impact of the physical setup of a stereo camera system in indoor environments. To do this, we present the results of an experimental analysis in which we use a given software setup to estimate the distance to an object while systematically changing the camera setup. thereby, we vary the three main parameters of the physical camera setup, namely the angle and distance between the cameras as well as the field of view. Based on the results, we derive several guidelines on how to choose the parameters for an application.

关键词： computer vision stereo camera mobile robotics distance estimation hardware modeling

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3d computer vision: From points to concepts 4th

3d computer vision: From points to concepts

引用

4th International conference on Pattern Recognition Applications and Methods, ICPRAM 2015

作者： Alexandre, Luís A. Department of Informatics and Instituto de Telecomunicações University of Beira Interior Covilhã Portugal

ISBN: (纸本)9783319276762

the emergence of cheap structured light sensors, like the Kinect, opened the door to an increased interest in all matters related to the processing of 3D visual data. Applications for these technologies are abundant, from robot vision to 3D scanning. In this paper we go through the main steps used on a typical 3D vision system, from sensors and point clouds up to understanding the scene contents, including key point detectors, descriptors, set distances, object recognition and tracking and the biological motivation for some of these methods. We present several approaches developed at our lab and some current challenges. © Springer International Publishing Switzerland 2015.

关键词： Object recognition

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An Efficient CADNet for Classification of High-frequency Oscillations in Magnetoencephalography 4

An Efficient CADNet for Classification of High-frequency Osc...

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4th International conference on robotics and computer vision, ICRCV 2022

作者： Zhang, Meijuan Liu, Jun Liu, Chuang Wu, Ting Peng, Xueping Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology School of Computer Science and Engineering Wuhan Institute of Technology Wuhan China Nanjing Brain Hospital Nanjing Medical University Department of Neurology Nanjing China University of Technology Sydney BroadwayNSW Australia

ISBN: (数字)9781665481700

ISBN: (纸本)9781665481700

Epilepsy is a chronic neurological disease, and locating the lesions precisely is crucial to the success of epilepsy surgery. the high-frequency oscillations (HFOs) in magnetoencephalography (MEG) of epileptic patients can be used to detect seizures. Due to the inefficient and error-prone operation of traditional HFOs detection, it is necessary to develop an approach for the detection of HFOs, which can automatically classify HFOs in MEG. In this paper, We proposed a novel deep learning-based CADNet for the classification of HFOs in MEG. First, we preprocessed acquired MEG data by short-time Fourier transform (STFT), and the extracted time-frequency domain information was applied for model training after pictorialism. then, we captured the features from these images through convolutional neural network combined with multi-head self-attention, all these features were input into Dendrite Net for classification. We evaluated our model on MEG dataset, and the accuracy, precision, recall, and F1-score of the optimized model reached 0.97, 0.98, 0.97, 0.97. We compared the proposed CADNet with other deep learning models, the result demonstrates that our model outperforms others. © 2022 IEEE.

关键词： Feature extraction

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Semantic Injection Infrared and Visible Image Fusion Via a Disentangled Representation Network 4

Semantic Injection Infrared and Visible Image Fusion Via a D...

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4th International conference on robotics and computer vision, ICRCV 2022

作者： Lu, Changkun Zhou, Huabing Wuhan Institute of Technology College of Computer Science and Engineering Wuhan China Wuhan Institute of Technology Hubei Key Laboratory of Intelligent Robot Wuhan China

ISBN: (数字)9781665481700

ISBN: (纸本)9781665481700

Image fusion is the task of generating images from the same scene with different sensors. Images obtained by different sensors have different expressions under the image target semantics. Good semantic aware images can better serve the subsequent advanced image processing tasks. Most of the existing fusion methods are based on the underlying logic of the image, without considering the high-level semantic fusion. We propose a semantic injection disentangled representation network SDR. the source image is decomposed into structural and modal features by the corresponding encoder, and a generator based on semantic injection is constructed to generate the fused image under Semantic injection. On the open data set, our fusion network is compared with eight most advanced methods. Qualitative and quantitative experiments show that our method is superior to the current most advanced fusion methods. the fusion result preserves the structural information of the infrared image and the texture details of the visible image. the model proposed in this paper combines the advantages of feature decoupling and semantic injection, and has a better effect on fused images. © 2022 IEEE.

关键词： Semantics

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Untangling Dense Knots by Learning Task-Relevant Keypoints 4

Untangling Dense Knots by Learning Task-Relevant Keypoints

引用

4th conference on robot Learning (CoRL)

作者： Grannen, Jennifer Sundaresan, Priya thananjeyan, Brijen Ichnowski, Jeffrey Balakrishna, Ashwin Hwang, Minho Viswanath, Vainavi Laskey, Michael Gonzalez, Joseph E. Goldberg, Ken Univ Calif Berkeley Berkeley CA 94720 USA Toyota Res Inst Los Altos CA USA

Untangling ropes, wires, and cables is a challenging task for robots due to the high-dimensional configuration space, visual homogeneity, self-occlusions, and complex dynamics. We consider dense (tight) knots that lack space between self-intersections and present an iterative approach that uses learned geometric structure in configurations. We instantiate this into an algorithm, HULK: Hierarchical Untangling from Learned Keypoints, which combines learning-based perception with a geometric planner into a policy that guides a bilateral robot to untangle knots. To evaluate the policy, we perform experiments both in a novel simulation environment modelling cables with varied knot types and textures and in a physical system using the da Vinci surgical robot. We find that HULK is able to untangle cables with dense figure-eight and overhand knots and generalize to varied textures and appearances. We compare two variants of HULK to three baselines and observe that HULK achieves 43.3% higher success rates on a physical system compared to the next best baseline. HULK successfully untangles a cable from a dense initial configuration containing up to two overhand and figure-eight knots in 97.9% of 378 simulation experiments with an average of 12.1 actions per trial. In physical experiments, HULK achieves 61.7% untangling success, averaging 8.48 actions per trial. Supplementary material, code, and videos can be found at https://***/y3a88ycu

关键词： Deformable Manipulation computer vision

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A Fast Detection Algorithm of Small Targets Based on YOLOv3 4

A Fast Detection Algorithm of Small Targets Based on YOLOv3

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4th IEEE Information Technology, Networking, Electronic and Automation Control conference (ITNEC)

作者： Zhang, Xu Yang, Lichao Huang, Rui Lyu, Juntao Li, Tao State Grid Intelligent Technol Co Ltd Shenzhen Peoples R China State Grid Shandong Elect Power Co Jinan Peoples R China

ISBN: (纸本)9781728143903

robots, endowed with computer vision function by on-board cameras and embedded systems, have become popular in the modem power industry. In order to realize automatic image analysis at the data acquisition part, a fast detection algorithm especially for small target based on YOLOv3 was proposed. It is proposed to up sample by 2 X feature map which is down sampled by 8 X of the previous network, and concatenate it with the output of the second Res block unit, and the last Res block unit of the previous network was abandoned. To obtain more features of the small target, add two Resnet units in the second Res block unit of Darknet53 in YOLO V3 network structure. Aiming at deploying the algorithm to the hardware, model pruning was applied to decrease model size and improve detection speed. the experimental results demonstrate that the mAP (Mean Average Precision) reaches 0.85, and the proposed algorithm is capable of real-time detection as faster than 15 frames per second (fps).

关键词： inspection robot object detecion small target detecion model pruning YOLOv3

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