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检索条件"任意字段=17th Image Processing: Algorithms and Systems Conference, IPAS 2019"

共 249 条记录，以下是51-60 订阅

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Hybrid CPU-GPU Solver for Gradient Domain processing of Massive images

Hybrid CPU-GPU Solver for Gradient Domain Processing of Mass...

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17th IEEE International conference on Parallel and Distributed systems (ICPADS)

作者： Philip, Sujin Summa, Brian Pascucci, Valerio Bremer, Peer-Timo Sci Comp & Imaging Inst Salt Lake City UT USA Lawrence Livermore Natl Lab Livermore CA USA

ISBN: (纸本)9780769545769

Gradient domain processing is a computationally expensive image processing technique. Its use for processing massive images, giga or terapixels in size, can take several hours with serial techniques. To address this challenge, parallel algorithms are being developed to make this class of techniques applicable to the largest images available with running times that are more acceptable to the users. To this end we target the most ubiquitous form of computing power available today, which is small or medium scale clusters of commodity hardware. Such clusters are continuously increasing in scale, not only in the number of nodes, but also in the amount of parallelism available within each node in the form of multicore CPUs and GPUs. In this paper we present a hybrid parallel implementation of gradient domain processing for seamless stitching of gigapixel panoramas that utilizes MPI, threading and a CUDA based GPU component. We demonstrate the performance and scalability of our implementation by presenting results from two GPU clusters processing two large data sets.

关键词： hybrid programming gpgpu cluster gradient domain image processing

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Object Tracking With A Robotic Manipulator Mounted On Ground Vehicle Using image Based Visual Servoing 17

Object Tracking With A Robotic Manipulator Mounted On Ground...

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17th International conference on Control, Automation and systems (ICCAS)

作者： Sami, Muhammad Ahsan Masood, Muhammad Umar Waqar, Muhammad Mujtaba, Muhammad Shah, Abrahim Ali Shujah, Adnan Rashid, Nasir Tiwana, Mohsin I. Iqbal, Javaid Natl Univ Sci & Technol Dept Mechatron Engn H12 Islamabad Pakistan

ISBN: (纸本)9788993215144

this paper presents an application of a novel approach for detecting and tracking an object with a 2 DOF robotic manipulator which can be equipped with an array of electrically controlled actuators. the said approach utilizes the image Based Visual Servoing (IBVS) technique. the developed system is able to determine the object pose in real time from features in the image. Object is detected using shaped based approach algorithms of image processing. the position and orientation of the world coordinates of the object being tracked are calculated from the coordinates of the object in image plane using camera's intrinsic and extrinsic parameters. Experimental results demonstrate the effectiveness of this proposed approach.

关键词： Robotic Manipulator image Jacobian Inverse Kinematics PID Canny Filter thresholding Object Detection Object Tracking

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A parallel implementation of an XDraw viewshed algorithm with spark 21

A parallel implementation of an XDraw viewshed algorithm wit...

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21st IEEE International conference on High Performance Computing and Communications, 17th IEEE International conference on Smart City and 5th IEEE International conference on Data Science and systems, HPCC/SmartCity/DSS 2019

作者： Jianbo, Zhang Caikun, Chen Tingnan, Liang Hao, Xia Simin, Zhou Faculty of Information Engineering China University of Geosciences Wuhan China

ISBN: (纸本)9781728120584

Viewshed analysis is an indispensable part of digital terrain analysis and is widely used in many application domains. High-resolution raster DEM data bring significant computational challenges to the existing viewshed analysis algorithms, which are computationally intensive and require a large memory space and massive computing power. the viewshed analysis process can be accelerated through the use of Apache Spark. In this article, we present both a tile-based raster data storing strategy and an equal-volume computing strategy for distributed viewshed computation using Spark. the parallel implementation of the XDraw algorithm mainly consists of three parts: (1) partitioning a raster DEM file into square tile sets and reorganizing these tile sets to prevent tile overlap across data divisions of HDFS, (2) subdividing the DEM into multiple equal-volume data sectors according to the viewpoint position, and (3) retrieving the corresponding tile sets of each sector to perform the XDraw algorithm independently and efficiently. Experiments with realworld datasets show that the two proposed strategies can achieve higher speed-up and efficiency for XDraw viewshed analysis as the raster DEM data volume is dramatically increased. © 2019 IEEE.

关键词： Sparks Partitioning algorithms Distributed databases Graphics processing units Geology Parallel processing Approximation algorithms

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Real-time Smart Stereo Camera based on FPGA-SoC 17

Real-time Smart Stereo Camera based on FPGA-SoC

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IEEE-RAS 17th International conference on Humanoid Robotics (Humanoids)

作者： Michalik, Soenke Michalik, Soeren Naghmouchi, Jamin Berekovic, Mladen TU Braunschweig D-38106 Braunschweig Germany

ISBN: (纸本)9781538646786

Stereo image processing is one of the most demanding tasks in the field of 3D computer vision and robot vision requiring high-performance computing capabilities within embedded systems. Real-time constraints for autonomous vehicles such as humanoid robots, lead to hardware acceleration approaches for high resolution stereo imaging in human-like vision systems, where commonly FPGA device are employed to handle very high sensor data rates. this work presents a real-time smart stereo camera system implementation resembling the full stereo processing pipeline in a single FPGA device. We introduce the novel memory optimized stereo processing algorithm "Sparse Retina Census Correlation" (SRCC) that embodies a combination of two well established window based stereo matching approaches. We have leveraged a Sum of Absolute Difference (SAD) of Sobel-filtered images and a Sum of Hamming Distance (SHD) using a modified Retina based Census Transform for increased robustness to lighting variations and for high accuracy. A color rectification module has been implemented to cope with the high frame rate of the stereo pipelining calculating image transformations and rectified pixel coordinates in real-time using parameters for camera intrinsic, image rotation, image distortion and image projection. In addition multiple post-processing algorithms like texture filtering, uniqueness filtering, speckle removal and disparity to depth conversion have been implemented to further enhance the output results. the presented smart camera solution has demonstrated real-time stereo processing of 1280x720 pixel depth images with 256 disparities on a Zynq XC7Z030 FPGA device at 60fps. Due to the universal USB3.0 UVC interface and the onboard depth calculation it is a replacement for RGBD 3D-Sensors with improved image quality and outdoor performance. the camera can easily be used in conjunction with ROS-enabled robots and in automotive or industrial applications.

关键词： Field programmable gate arrays Cameras Robot sensing systems Correlation Transforms Real-time systems

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G-match: A fast GPU-friendly data compression algorithm 21

G-match: A fast GPU-friendly data compression algorithm

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作者： Lu, Li Hua, Bei School of Computer Science and Technology University of Science and Technology of China Hefei Anhui China

ISBN: (纸本)9781728120584

Data compression plays an important role in the era of big data;however, such compression is typically one of the bottlenecks of a massive data processing system due to intensive computing and memory access. In this paper, we propose a high-speed GPU-friendly data compression algorithm called G-match that takes full advantage of the GPU parallel computing power to speed up the compression process. the greatest challenge here is to solve the contradiction between the high data dependency inherent in the compression algorithm and the GPU single-instruction multiple-thread operating model. G-match achieves a high parallel degree by eliminating fine-grained data dependency and all path divergences in the algorithm. Compared with other, similar work on GPUs, G-match is the first thoroughly parallelized data compression algorithm. Experiments comparing other GPU compression algorithms show that G-match achieves approximately 33% speedup over the current fastest implementation and the highest compression ratio. © 2019 IEEE.

关键词： Graphics processing unit

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Budget constraint roadside units placement for traffic flows monitoring system with reliability in vehicular networks 21

Budget constraint roadside units placement for traffic flows...

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作者： Jiang, Peng Li, Peng Zhang, Tao Huang, Weiyi He, Heng Nie, Lei Liu, Qin College of Computer Science and Technology Wuhan University of Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing Real-time Industrial System China Department of Computer Science New York Institute of Technology United States School of Cyber Science and Engineering Wuhan University China

ISBN: (纸本)9781728120584

In Traffic Flows Monitoring System (TFMS), the key problem is how to install Roadside Units (RSUs) reliably to monitor traffic flows with the constrained budget. the reliability of Traffic Flows Monitoring System(TFMS) is determined by the number of RSUs each traffic flow pass through, and the RSUs placement number is determined by the budget and the placement strategy. In this paper, we investigate the budget constraint RSUs placement problem for traffic flows monitoring system with reliability in vehicular networks. Given a budget constraint, the problem is how to install RSUs to ensure the reliability of TFMS, that is each traffic flow pass through RSUs as many as possible with the limited budget. We prove that this problem is NP-hard. then, we propose two greedy algorithms to solve the problem according to the pigeonhole principle. Moreover, approximation ratios of proposed algorithms are given. Finally, we verify the feasibility of proposed algorithms through extensive experiments, and the results show that the proposed algorithms are superior to the other algorithms. © 2019 IEEE.

关键词： Reliability

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Parallel hybrid join algorithm on GPU 21

Parallel hybrid join algorithm on GPU

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作者： Guo, Chengxin Chen, Hong Zhang, Feng Li, Cuiping Key Lab of Data Engineering and Knowledge Engineering Ministry of Education School of Information Renmin University of China Beijing China

ISBN: (纸本)9781728120584

In data analytics applications, join is a general and time consuming operation. Optimizing join algorithms can benefit the query processing significantly. the emerging of GPUs provides a massive parallelism solution for improving the performance of the join operation. the hash join (HJ) and sort merge join (SMJ), which are two widely used join algorithms, have been proved effective for efficient join processing on the GPUs. Both algorithms have their own advantages and drawbacks, offering the chance of combining the advantages of HJ and SMJ on GPUs. In processing join operation on GPUs, data need to be transmitted between the CPU and the GPU due to the discrete GPU memory design, which causes performance degradation because of the high PCIe data transfer overhead. As GPUs are becoming more powerful than before, the performance gap between data transmission and GPU execution increases, which makes it even harder to implement an efficient join on GPUs. In this paper, we focus on the optimization of join algorithms on GPUs. We propose the Parallel Hybrid Join algorithm on GPUs(PHYJ) to combine the advantages of HJ and SMJ, and overlap the data communication and GPU execution with a pipeline mechanism. In our evaluation, the PHYJ shows up to 1.72X and 1.55X speedup over the up-to-date HJ and SMJ algorithms respectively on a NVIDIA GTX 1080ti-Pascal GPU. On the TitanV-Volta GPU, up to 1.54X and 1.42X improvements can be achieved over the baseline HJ and SMJ algorithms respectively. © 2019 IEEE.

关键词： Graphics processing unit

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Development Approaches of Cloud-Based System for Object Recognition on images 17

Development Approaches of Cloud-Based System for Object Reco...

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17th IEEE International conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering, TCSET 2024

作者： Bershchanskyi, Yevhen Klym, Halyna Lviv Polytechnic National University Department of Specialized Computer Systems Lviv Ukraine

ISBN: (纸本)9798331520564

Object recognition systems have become integral in various domains, enhancing automation and decision-making processes. this research focuses on developing a cloud-based system specifically designed for efficient object recognition in images. Leveraging the scalability and flexibility of cloud computing, the proposed system not only performs accurate object detection but also ensures secure and scalable image storage. Implemented on the Amazon Web Services (AWS) platform, the system integrates advanced AI algorithms with cloud-native technologies to optimize resource usage and automate workload management. Key contributions include the design of a robust architecture that balances computational loads, enhances recognition accuracy, and streamlines image processing. this study demonstrates the potential of cloud technologies in simplifying object recognition tasks while maintaining security and efficiency. © 2024 IEEE.

关键词： Cloud platforms

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Word image representation based on sequence to sequence model with attention mechanism for out-of-vocabulary keyword spotting 21

Word image representation based on sequence to sequence mode...

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作者： Wei, Hongxi Kang, Yanke Zhang, Hui School of Computer Science Inner Mongolia University Hohhot China Provincial Key Laboratory of Mongolian Information Processing Technology Hohhot China

ISBN: (纸本)9781728120584

To realize keyword spotting by means of query-by-example, learning efficient representation for word images is an essential issue. However, the amount of vocabulary at the training stage is often far less than the complete vocabulary of a certain language in various learning based representation approaches. thus, unseen vocabularies might be taken as query keywords which may not exist in training set. therefore, out-of-vocabulary (OOV) is frequently occurred in keyword spotting. In this paper, a sequence to sequence model with attention mechanism has been proposed to generate representation vectors of word images for solving the problem of OOV. After that, similarities can be calculated between each word image and a given query keyword image on their representation vectors. And then, a ranking list can be formed in descending order of the similarities for a collection of word images. Experimental results demonstrate that the proposed representation approach can be competent for the task of OOV keyword spotting and outperforms various baseline and state-of-the-art methods. © 2019 IEEE.

关键词： image representation

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A New Pixel-based Fusion Framework to Enhance Object Detection in Automotive Applications 17

A New Pixel-based Fusion Framework to Enhance Object Detecti...

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17th International conference on Information Fusion (FUSION)

作者： thomanek, Jan Wanielik, Gerd Ingenieurgesellsch Auto & Verkehr GmbH D-10587 Berlin Germany Tech Univ Chemnitz D-09107 Chemnitz Germany

ISBN: (纸本)9781479916344

Modern cooperative Advanced Driver Assistance systems (ADASs) require efficient algorithms and methods for the real-time processing of all sensor data. In particular, systems for combination of different sensors are gaining increasing importance. this paper proposes an early fusion technique to combine the advantages of two or more vision sensors. It creates a single composite image that will be more comprehensive for further computer vision tasks, e.g. Object Detection. After image registration, the presented pixel-based fusion framework transforms the registered sensor images into a common representational format by a multiscale decomposition. A denoising and a multiscale edge detection are applied on the transformed data. Only data with a high Activity Level are considered for the fusion process that based on a probabilistic approach. Finally, the fused image can be the input for a subsequent feature extraction task. the proposed fusion technique is examined on a Pedestrian Detection System based on an infrared and a visible light camera.

关键词： Cameras Feature extraction image edge detection Object detection Wavelet domain Wavelet transforms Object detection Edge detection Wavelet domain Cameras wavelet transforms Feature extraction Automotive applications images Fusion reactions FUSION fusion (melting) Fusion, biological Sensor Data COMPOSITE imageS vision sensors

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