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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems III"

共 14693 条记录，以下是4291-4300 订阅

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Robust Visual-Inertial State Estimation with Multiple Odometries and Efficient Mapping on an MAV with Ultra-Wide FOV Stereo Vision

Robust Visual-Inertial State Estimation with Multiple Odomet...

引用

25th IEEE/RSJ International conference on Intelligent Robots and systems (IROS)

作者： Mueller, M. G. Steidle, F. Schuster, M. J. Lutz, P. Maier, M. Stoneman, S. Tomic, T. Stuerzl, W. German Aerosp Ctr DLR Inst Robot & Mechatron Cologne Germany Skydio Inc Redwood City CA USA

ISBN: (纸本)9781538680940

The here presented flying system uses two pairs of wide-angle stereo cameras and maps a large area of interest in a short amount of time. We present a multicopter system equipped with two pairs of wide-angle stereo cameras and an inertial measurement unit (IMU) for robust visual-inertial navigation and time-efficient omni-directional 3D mapping. The four cameras cover a 240 degree stereo field of view (FOV) vertically, which makes the system also suitable for cramped and confined environments like caves. In our approach, we synthesize eight virtual pinhole cameras from four wide-angle cameras. Each of the resulting four synthesized pinhole stereo systems provides input to an independent visual odometry (VO). Subsequently, the four individual motion estimates are fused with data from an IMU, based on their consistency with the state estimation. We describe the configuration and image processing of the vision system as well as the sensor fusion and mapping pipeline on board the MAV. We demonstrate the robustness of our multi-VO approach for visual-inertial navigation and present results of a 3D-mapping experiment.

关键词： Cameras Distortion image resolution Computational modeling Navigation Visual odometry Hardware

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Multibeam Data processing for Underwater Mapping

Multibeam Data Processing for Underwater Mapping

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25th IEEE/RSJ International conference on Intelligent Robots and systems (IROS)

作者： Teixeira, Pedro V. Kaess, Michael Hover, Franz S. Leonard, John J. MIT Dept Mech Engn 77 Massachusetts Ave Cambridge MA 02139 USA Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA

ISBN: (纸本)9781538680940

From archaeology to the inspection of subsea structures, underwater mapping has become critical to many applications. Because of the balanced trade-off between range and resolution, multibeam sonars are often used as the primary sensor in underwater mapping platforms. These sonars output an image representing the intensity of the received acoustic echos over space, which must be classified into free and occupied regions before range measurements are determined and spatially registered. Most classifiers found in the underwater mapping literature use local thresholding techniques, which are highly sensitive to noise, outliers, and sonar artifacts typically found in these images. In this paper we present an overview of some of the techniques developed in the scope of our work on sonar-based underwater mapping, with the aim of improving map accuracy through better segmentation performance. We also provide experimental results using data collected with a DIDSON imaging sonar that show that these techniques improve both segmentation accuracy and robustness to outliers.

关键词： Sonar measurements Robot sensing systems Acoustic beams image segmentation Mathematical model Acoustics

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Effective denoising with non-local means filter for reliable unwrapping of digital holographic interferometric fringes 1

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2nd International conference on Computer Vision and image processing, CVIP 2017

作者： Aparna, P.L. Waghmare, Rahul G. Mishra, Deepak Sai Subrahmanyam Gorthi, R.K. National Institute of Technology Surathkal575025 India Indian Institute of Space Science and Technology Trivandrum695547 India Indian Institute of Technology Tirupati517506 India

ISBN: (数字)9789811078958

ISBN: (纸本)9789811078941

Estimation of phase from the complex interference field has become an emerging area of research for last few decades. The phase values obtained by using arctan function are limited to the interval (-π, π]. Such phase map is known as wrapped phase. The unwrapping process, which produces continuous phase map from the wrapped phase, becomes tedious in presence of noise. In this paper, we propose a preprocessing technique that removes the noise from the interference field, thereby improving the performance of naive unwrapping algorithms. For de-noising of the complex field, real part and imaginary parts of the field are processed separately. Real-valued images (real and imaginary parts) are processed using non-local means filter with non-Euclidian distance measure. The de-noised real and imaginary parts are then combined to form a clean interference field. MATLAB’s unwrap function is used as unwrapping algorithm to get the continuous phase from the cleaned interference field. Comparison with the Frost’s filter validates the applicability of proposed approach for processing the noisy interference field. © 2018, Springer Nature Singapore Pte Ltd.

关键词： image denoising

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image Filtering Enhancement 9th

Image Filtering Enhancement

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9th International conference on Swarm Intelligence (ICSI)

作者： Guo, Zhen Pan, Hang Chen, Jinlong Chen, Xianjun Guilin Univ Elect Technol Guangxi Key Lab Cryptog & Informat Secur Guilin 541004 Guangxi Peoples R China Guilin Univ Elect Technol Key Lab Intelligent Proc Comp Image & Graph Guilin 541004 Guangxi Peoples R China Haikou Coll Econ Informat Engn Sch Haikou 571127 Hainan Peoples R China

ISBN: (纸本)9783319938189;9783319938172

With the development of science and technology, mankind has entered the information age. image has become the main source of human access to information. However, in the actual process of image signal transmission, the loss and damage of data packet are inevitable due to the physical defects of the channel, which lead to a serious decline in the quality of the video stream. So it is necessary and even urgent now to do some research work on image enhancement technology. In this paper, the image enhancement algorithms that are commonly used, such as bilateral filtering algorithm, homomorphic filtering algorithm, are analyzed in image processing. In the design of the image enhancement, the best modeling and design schemes are chosen according to the comparison. The experimental results demonstrate that the bilateral filtering algorithm can effectively maintain the details of the image edges and make the image more smooth;the homomorphic filtering algorithm can effectively adjust the image gray range, so that the image details on the image area can be increased, and the algorithm can handle the image with inhomogeneous intensity. This work will lay a good foundation of further research.

关键词： image enhancement Homomorphic filtering Bilateral filtering

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International conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)

作者： Rahul Suresh N Keshava RV College of Engineering R V Vidyanikethan Post Mysuru Road Bengaluru Karnataka India

ISBN: (数字)9781728126197

ISBN: (纸本)9781728126203

image processing has made huge progress in recent times and has captured the attention of the international research community in recent times. In this survey paper the winning Convolutional Neural Network (CNN) architectures of the popular imageNet Large Scale Visual Recognition Competition (ILSVRC) competition along with the innovations they introduced are discussed in detail. CNNs to the likes of the ZFNet, Inception V1, V2, V3 and V4 versions, ResNet versions, Inception ResNet versions, VGG versions are all covered. Also object detection is looked at as a preeminent task and popular models like RCNN, Fast RCNN, Faster RCNN and the YOLO versions along with their award winning architectures are discussed. Text classification is another major practice that is followed before making business decisions. In this survey paper section iii explains the text classification techniques. preprocessing techniques such as removing stop words, stemming, lemmatization. Two variants of vectorization method such as vectorization-delta, vectorization-center. paper also explains the hyperparameter tuning for optimization of support vector machine(SVM), Logistic regression(LR), random forest(RF) and Boosted Regression Tree (BRT). Explored fine tuning parameter which enhance the performance of machine learning models.

关键词： Training Object detection Task analysis Machine learning Kernel Computer architecture Technological innovation

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Score and Rank-Level Fusion for Emotion Recognition Using Genetic Algorithm 17

Score and Rank-Level Fusion for Emotion Recognition Using Ge...

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17th IEEE International conference on Cognitive Informatics and Cognitive Computing (ICCI*CC)

作者： Ahmed, Ferdous Sieu, Brandon Gavrilova, Marina L. Univ Calgary Dept Comp Sci Calgary AB Canada

ISBN: (纸本)9781538633601

Analysis of human body movement reveals information pertinent to efficient modeling of human behavior. Identification of the most contributing features, known to perform well in recognizing emotions, is a difficult task. This article proposes to use the binary chromosome based genetic algorithm to determine a subset of features that maximizes the accuracy of four expert systems developed for emotion recognition. The approach also identifies essential features for each of the expert models by selecting the minimum subset required to maximize the recognition accuracy. Later, the expert models are fused using score-level and rank-level fusion algorithms to further improve the performance of the system. Fusion of the expert models achieved an overall emotion recognition rate of 80% on a Kinect gait database.

关键词： Emotion Recognition Information Fusion Gait Analysis Genetic Algorithm image and Video processing Cognitive Processes

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ACE: An Efficient Asynchronous Corner Tracker for Event Cameras 6

ACE: An Efficient Asynchronous Corner Tracker for Event Came...

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6th International conference on 3D Vision (3DV)

作者： Alzugaray, Ignacio Chli, Margarita Swiss Fed Inst Technol Vis Robot Lab Zurich Switzerland

ISBN: (纸本)9781538684252

The emergence of bio-inspired event cameras has opened up new exciting possibilities in high frequency tracking, overcoming some of the limitations of traditional frame-based vision (e.g. motion blur during high-speed motions or saturation in scenes with high dynamic range). As a result, research has been focusing on the processing of their unusual output: an asynchronous stream of events. With the majority of existing techniques discretizing the event-stream into frame-like representations, we are yet to harness the true power of these cameras. In this paper, we propose the ACE tracker: a purely asynchronous framework to track corner-event features. Evaluation on benchmarking datasets reveals significant improvements in accuracy and computational efficiency in comparison to state-of-the-art event-based trackers. ACE achieves robust performance even in challenging scenarios, where traditional frame-based vision algorithms fail.

关键词： Cameras Tracking image edge detection Simultaneous localization and mapping Feature extraction Robot vision systems Visualization

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Automatic Detection of Cells in FISH images Using Map of Colors and Three-Track Segmentation 20th

Automatic Detection of Cells in FISH Images Using Map of Col...

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20th Polish conference on Biocybernetics and Biomedical Engineering (PCBBE)

作者： Les, Tomasz Markiewicz, Tomasz Patera, Janusz Warsaw Univ Technol Warsaw Poland Mil Inst Med Warsaw Poland

ISBN: (纸本)9783319669052

The article presents a complex method of recognition nuclei cells areas and of segmentation of nuclei. The evaluation process of the identification and segmentation quality of proposed methods using L2 distance function and sensitivity function is also presented. FISH test is a fluorescence technique used for staining of microscope images of breast cancer. The technique allows visualization of HER2, CEN17 genes and cells nuclei. Fast and efficient microscopy image analysis allows a proper choice of therapy. This article presents a new, complex technique based on the color analysis, morphological transformations and watershed segmentation. The technique allows rapid and efficient identification of nuclei areas, as well as precise detection of the cells nuclei outlines. This step is often overlooked in a computer image analysis, whereas it is extremely important. It allows to increase the accuracy of HER2/ CEN17 gene detection, as well as it allows to exclude fake biomarkers and increase the speed of identification of algorithms for HER2 genes by limiting the searched area. Proper segmentation of nuclei also makes manual evaluation of images easier.

关键词： Signal and image processing Object recognition FISH images Cell nucleus identification and segmentation

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DEVELOPMENT AND VALIDATION OF A GNC ALGORITHM USING A STEREOSCOPIC IMAGING SENSOR IN CLOSE PROXIMITY OPERATIONS

DEVELOPMENT AND VALIDATION OF A GNC ALGORITHM USING A STEREO...

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AAS/AIAA Astrodynamics Specialist conference

作者： Davis, Jill Galchenko, Pavel Jennings, Donna Pernicka, Henry Missouri Univ Sci & Technol Mech & Aerosp Engn 400 W 13th St Rolla MO 65409 USA Missouri Univ Sci & Technol Aerosp Engn Mech & Aerosp Engn 400 W 13th St Rolla MO 65409 USA

ISBN: (纸本)9780877036456

The stereoscopic imaging system used for conducting proximity operations with an inspector satellite near a noncooperative resident space object is validated using AGI's systems Tool Kit and the MATLAB environment. The guidance, navigation, and control algorithms of the system are implemented using MATLAB, while an STK scenario acts as the truth model and provides the algorithms with sensor data. STK is also used for the graphical modeling and visualization. The stereoscopic imaging cameras are modeled in STK as conical sensors with specified fields of view. Custom angles created in STK then provide real time bearing angle data to the navigation filter, which determines the position, velocity, and attitude of the inspector satellite and the relative position and velocity of the nRSO using complementary sensor data. These data are also extracted from the STK model through the MATLAB/Connect data provider commands, and include magnetometer, IMU, GPS, and Sun sensor data.

关键词： Stereo image processing

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Online Inference and Detection of Curbs in Partially Occluded Scenes with Sparse LIDAR

Online Inference and Detection of Curbs in Partially Occlude...

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International conference on Intelligent Transportation

作者： Tarlan Suleymanov Lars Kunze Paul Newman Oxford Robotics Institute (ORI) Dept. of Engineering Science University of Oxford Oxford UK

Road boundaries, or curbs, provide autonomous vehicles with essential information when interpreting road scenes and generating behaviour plans. Although curbs convey important information, they are difficult to detect in complex urban environments (in particular in comparison to other elements of the road such as traffic signs and road markings). These difficulties arise from occlusions by other traffic participants as well as changing lighting and/or weather conditions. Moreover, road boundaries have various shapes, colours and structures while motion planning algorithms require accurate and precise metric information in real-time to generate their *** this paper, we present a real-time LIDAR-based approach for accurate curb detection around the vehicle (360 degree). Our approach deals with both occlusions from traffic and changing environmental conditions. To this end, we project 3D LIDAR pointcloud data into 2D bird's-eye view images (akin to Inverse Perspective Mapping). These images are then processed by trained deep networks to infer both visible and occluded road boundaries. Finally, a post-processing step filters detected curb segments and tracks them over time. Experimental results demonstrate the effectiveness of the proposed approach on real-world driving data. Hence, we believe that our LIDAR-based approach provides an efficient and effective way to detect visible and occluded curbs around the vehicles in challenging driving scenarios.

关键词： Roads Laser radar Three-dimensional displays Shape Training data Machine learning image segmentation

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