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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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Heterogeneous FPGA-based System for Real-Time Drowsiness Detection 17

Heterogeneous FPGA-based System for Real-Time Drowsiness Det...

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17th conference on Ph.D Research in Microelectronics and Electronics (PRIME)

作者： Migali, Andrea Spagnolo, Fanny Corsonello, Pasquale Univ Calabria Dept Informat Modeling Elect & Syst Engn I-87036 Arcavacata Di Rende Italy

ISBN: (纸本)9781665467001

Drowsiness detection is a key feature in modern Advanced Driver Assistance systems (ADAS). State-of-the-art approaches rely on machine learning techniques and neural networks to monitor unusual movements of the head and eyes activities. Unfortunately, due to their computationally intensive operations, integrating such algorithms in real-time and low-power operating scenarios, like automotive applications, is still quite challenging. this paper proposes an efficient hardware architecture for real-time drowsiness detection based on monitoring the driver's eye blinking behaviour through the PERcentage of eye CLOSure (PERCLOS) metric. Experimental results obtained on the Xilinx Zynq XC7Z020 FPGA SoC show that the proposed system is up to 33.3 times faster and 2.6 times less area consuming than state-of-the-art competitors.

关键词： Drowsiness detection ADAS real-time image processing FPGA

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Mobile-cloud data processing system on digital images 17

Mobile-cloud data processing system on digital images

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17th IEEE International conference on Industrial Informatics (INDIN)

作者： Samoylov, Alexey Borodyansky, Yuri Kostyuk, Andrei Polovko, Ivan Southern Fed Univ Inst Comp Technol & Informat Secur Taganrog Russia

ISBN: (纸本)9781728129273

the quality of measurements in modern photogrammetric complexes essentially depends on the selected scale of the survey, the location of the imaging cameras, the object's own shape, and also the limitations imposed by the survey conditions. therefore, to ensure the required quality metrics in each specific case, it is necessary to solve the task of selecting the number, parameters and location of cameras for a given class of objects. the reason for the limited possibilities lies in the rigid fixing of the bundle of technical devices and the rules for processing images from them. At the same time, the creation of photogrammetric complexes by default implies the availability of specialized software, and the development of methods for computer image processing, the performance of graphics processors and personal devices (laptops, tablets, etc.) makes it possible to expand the functionality of this provision. Existing program components of photogrammetric complexes represent a bunch of means of preliminary processing, pattern recognition and solving countable problems in their various variations. Despite the existence of such a basic structure, software packages are built heuristically, and the set and sequence of interaction of the facilities are static. the article proposes a mobile cloud system that allows minimizing hardware requirements by implementing photogrammetry algorithms for image processing and analysis in the form of cloud services.

关键词： Photogrammetry cloud computing service pipe industry forest industry mobile application

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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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Real-time trajectory similarity processing using longest common subsequence 21

Real-time trajectory similarity processing using longest com...

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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： Ding, Jiafeng Fang, Junhua Zhang, Zonglei Zhao, Pengpeng Xu, Jiajie Zhao, Lei School of Computer Science Technology Soochow University Suzhou China

ISBN: (纸本)9781728120584

Driven by the fast development of mobile internet and mobile devices, huge volumes of trajectory data describing the spatial-temporal information of moving objects are currently generated. Trajectory similarity processing is playing a critical role to explore valuable information, such as the patterns of human activities and behaviors. However, most of the existing works optimize this operation in an off-line manner, which is unable to provide timely feedback for time-sensitive applications. In this paper, we present a new real-time processing framework for trajectory similarity measurement, with practical algorithms to reduce the computing resource cost and guarantee the correctness of the result. Our proposal includes a cost-effective framework to ensure the correctness of trajectory similarity processing, a stream partition algorithm to maximize the processing throughput, a lightweight Top-k computing mode to cut off unnecessary network cost. Empirical studies on real-world stream applications validate the usefulness of our proposals and prove the huge advantage of our approaches over state-of-the-art solutions in the literature. © 2019 IEEE.

关键词： Cost effectiveness

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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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Low level feature selection for a content based digital mammography image retrieval system

Low level feature selection for a content based digital mamm...

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2009 IEEE 17th Signal processing and Communications Applications conference, SIU 2009

作者： Öztürk, Özlem Bulu, Hakan Alpkoçak, Adil Güzelis, Cüneyt Bilgisayar Mühendisligi Bölümü Turkey Elektrik ye Elektronik Mühendisligi Bölümü Dokuz Eylül Üniversitesi Turkey

ISBN: (纸本)9781424444366

Content Based image Retrieval (CBIR) systems enables to retrieve images from large image archieves based on its contents as well as external attributes associated to each image. this study aims at extracting low level attributes to be used in a CBIR model that enables the utilization of low level image based attributes together with high level concepts. the contribution of this study is to develop an infrastructure for the selection of best low level attribute set to be used in the CBIR method by considering model performance. Within the scope of this study: segmentation of mammogram images, development of a mammogram database, low level attribute extraction from the segmented images and breast type estimation by means of machine learning algorithms are realized. ©2009 IEEE.

关键词： Learning algorithms

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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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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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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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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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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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