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检索条件"任意字段=IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing"

共 120 条记录，以下是31-40 订阅

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Clustering and Visualization of Geodetic Array Data Streams using Self-Organizing Maps

Clustering and Visualization of Geodetic Array Data Streams ...

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ieee symposium on computational intelligence for multimedia, signal and vision processing (CIMSIVP)

作者： Popovici, Razvan Andonie, Razvan Szeliga, Walter M. Melbourne, Timothy I. Scrivner, Craig W. Altair Engn Inc Troy MI 48083 USA Oakland Univ Dept Comp Sci & Engn Rochester MI 48309 USA Cent Washington Univ Dept Comp Sci Ellensburg WA USA Transylvania Univ Brasov Elect & Computers Dept Brasov Romania Cent Washington Univ Dept Geol Sci Ellensburg WA USA

ISBN: (纸本)9781479945030

The Pacific Northwest Geodesic Array at Central Washington University collects telemetered streaming data from 450 GPS stations. These real-time data are used to monitor and mitigate natural hazards arising from earthquakes, volcanic eruptions, landslides, and coastal sea-level hazards in the Pacific Northwest. Recent improvements in both accuracy of positioning measurements and latency of terrestrial data communication have led to the ability to collect data with higher sampling rates. For seismic monitoring applications, this means 1350 separate position streams from stations located across 1200 km along the West Coast of North America must be able to be both visually observed and automatically analyzed at a sampling rate of up to 1 Hz. Our goal is to efficiently extract and visualize useful information from these data streams. We propose a method to visualize the geodetic data by clustering the signal types with a Self-Organizing Map (SOM). The similarity measure in the SOM is determined by the similarity of signals received from GPS stations. signals are transformed to symbol strings, and the distance measure in the SOM is defined by an edit distance. The symbol strings represent data streams and the SOM is dynamic. We overlap the resulted dynamic SOM on the Google Maps representation.

关键词： data visualisation geodesy geophysics computing pattern clustering self-organising feature maps Central Washington University GPS stations Google Maps representation Pacific Northwest Geodesic Array SOM similarity measure data stream clustering data stream visualization edit distance geodetic array data streams self-organizing maps signal similarity symbol strings telemetered streaming data Data visualization Earthquakes Educational institutions Global Positioning System Monitoring Real-time systems Vectors

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Toward under-specified queries enhancement using retrieval and classification platforms

Toward under-specified queries enhancement using retrieval a...

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ieee symposium on computational intelligence for multimedia, signal and vision processing (CIMSIVP)

作者： Mustapha, Aouache Hussain, Aini Samad, Salina Abdul Zulkifley, Mohd Asyraf Univ Kebangsaan Malaysia Fac Engn & Built Environm Dept Elect Elect & Syst Engn Bangi 43600 Selangor De Malaysia

ISBN: (纸本)9781479945030

Radiography images are used usually for diseases detection and fracture that can be visible on lateral view. Poor contrast of x-ray images do not provide momentous information concerning pathologies that are of interest to the radiologist. Magnification of contrast and sharpness of x-ray images will afford plenty and satisfactory visual information to radiologist and clinician and thus, allow better segmentation and indexing subsequent modules in the computer aided diagnosis (CAD) system for an autonomous disease diagnosis. Therefore, in this paper it intends to describe a new strategy to cater for under-specified queries enhancement using retrieval and classification platforms. In the retrieval platform (RPF), gamma correction (GC) function was employed on the under-specified query (USQ) image to generate dispersion versus location (DL) descriptor that measures the relationship between the local contrast and the local brightness, measured respectively with the help of estimators of location and dispersion. Subsequently, it employs appropriate near optimal search between the DL features of the USQ image and the corresponding similarity measurement in the archive database. In the classification platform (CPF), an approach was examined to predict the gain value of GC function using statistical pixel-level (SPL) features extracted from the radiography images along with the ANNs model classifier. The quality of the retrieved image is determined by referring to the USQ image. In addition, the problem of gain value estimation is transformed to a classification problem solved using an ANN model with three different measurement modes. Results indicated that the proposed approach can significantly improved image quality as confirmed by the DL descriptor which shown a more balance condition.

关键词： diagnostic radiography feature extraction image classification image enhancement image retrieval image segmentation medical image processing neural nets patient diagnosis ANN model CAD system CPF DL descriptor GC function RPF SPL features extraction USQ Xray image autonomous disease diagnosis computer aided diagnosis dispersion versus location descriptor gamma correction image classification platform image retrieval platform radiography image statistical pixel-level under-specified query image enhancement Databases Feature extraction Image quality Medical diagnostic imaging Predictive models Visualization

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Effective Dimensionality Reduction in multimedia Applications

Effective Dimensionality Reduction in Multimedia Application...

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ieee symposium on computational intelligence in Image and signal processing

作者： Jeong, Seungdo Kim, Sang-Wook Kim, Whoi-Yul Choi, Byung-Uk Hanyang Univ Dept Elect & Comp Engn Seoul 133791 South Korea

ISBN: (纸本)9781424427604

In multimedia information retrieval, multimedia data such as images and videos are represented as vectors in high-dimensional. space. To search these vectors efficiently, a variety of indexing methods have been proposed. However, the performance of these indexing methods degrades dramatically with increasing dimensionality, which is known as the dimensionality curse. To resolve the dimensionality curse, dimensionality reduction methods have been proposed. They map feature vectors in high-dimensional space into vectors in low-dimensional space before the data are indexed. This paper proposes an improvement for the previously proposed dimensionality reduction. The previous method uses the norm and the approximated angle for every subvector. However, more storage space and a number of cosine computations are required because of multiple angle components. In this paper, we propose an alternative method employing a single angle component instead of respective angles for all the subvectors. Because only one angle for every subvector is considered, though the loss of information regarding the original data vector increases, which degrades the performance slightly, we can successfully reduce storage space as well as a number of cosine computations. Finally, we verify the superiority of the proposed approach via extensive experiments with synthetic and real-life data sets.

关键词： Vectors

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A heterogeneous processing (HP) framework for multimedia query processing

A heterogeneous processing (HP) framework for multimedia que...

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1995 Heterogeneous Computing Workshop, HCW 1994

作者： Khokhar, Ashfaq Ghafoor, Arif Distributed Multimedia Systems Lab. School of Electrical Engineering Purdue University West LafayetteIN47907 United States

ISBN: (纸本)0818655925

In this paper, we define a novel system based on a hierarchical computational and data abstraction model to handle multimedia queries involving face recognition, scene matching, and speech recognition. For this purpose, the system integrates the state of the art research in diverse areas in computational sciences, including parallel processing, computer vision and image processing, artificial intelligence, multimedia databases, and speech and signal processing. This system uses a heterogeneous processing framework consisting state of the art image understanding and signal processing algorithms in addition to content-based retrieval techniques. These algorithms comprise of parallel coarse grained (MIMD) symbolic and fine grained (SIMD) numeric algorithms at various levels of this hierarchical model. © 1994 ieee.

关键词： Content based retrieval

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TOWARDS A UNIFIED FRAMEWORK FOR HAND-BASED METHODS IN FIRST PERSON vision.

TOWARDS A UNIFIED FRAMEWORK FOR HAND-BASED METHODS IN FIRST ...

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ieee International Conference on multimedia & Expo Workshops (ICMEW)

作者： Betancourt, Alejandro Morerio, Pietro Marcenaro, Lucio Barakova, Emilia Rauterberg, Matthias Regazzoni, Carlo Univ Genoa Dept Naval Elect Elect & Telecommun Engn Informat & Signal Proc Cognit Telecommun Grp I-16126 Genoa Italy Eindhoven Univ Technol Dept Ind Design Designed Intelligence Grp Eindhoven Netherlands

ISBN: (纸本)9781479970797

First Person vision (Egocentric) video analysis stands nowadays as one of the emerging fields in computer vision. The availability of wearable devices recording exactly what the user is looking at is ineluctable and the opportunities and challenges carried by this kind of devices are broad. Particularly, for the first time a device is so intimate with the user to be able to record the movements of his hands, making hand-based applications for First Person vision one the most explored area in the field. This paper explores the more popular processing steps to develop hand-based applications, and proposes a hierarchical structure that optimally switches between each of the levels to reduce the computational cost of the system and improve its performance.

关键词： Hand-detection Hand-segmentation Hand-identification Hands interactions First Person vision Egovision Werable cameras

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Bare bones strategy for human detection and tracking

Bare bones strategy for human detection and tracking

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ieee symposium on computational intelligence in Image and signal processing

作者： Siddiqui, M. N. Yousaf, B. Natl Univ Comp & Emerging Sci Islamabad Pakistan

ISBN: (纸本)9781424407071

we present a scaled down version of a Human Detection and Tracking System designed to run on relatively low-end machines of developing countries. The system uses sequence of monocular images of a single, fixed surveillance camera to extract data of moving objects. A Linear Motion Model coupled with Pre-computed Average Color Intensities is used to track the detected subjects across a series of frames. Head Detection algorithm is applied to form multiple hyotheses so as to accurately detect individuals in case of occlusion caused by people overlapping with each other. A final Shape Fitting algorithm is applied on the detected form to verify each hypothesis. Experiments conducted on real world data show the robustness of the algorithm, the speed of the process and its potential in lightweight, economical real- time applications.

关键词： computer vision feature extraction image colour analysis image motion analysis image sequences object detection surveillance target tracking color intensity head detection human detection human tracking linear motion model monocular image sequence moving image sequences image motion analysis COLOR STRENGTH image colour analysis Object detection Target tracking Moving computer vision Feature extraction Detective cameras

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Deep Aggregation of Regional Convolutional Activations for Content Based Image Retrieval 21

Deep Aggregation of Regional Convolutional Activations for C...

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ieee 21st International Workshop on multimedia signal processing (MMSP)

作者： Schall, Konstantin Barthel, Kai Uwe Hezel, Nico Jung, Klaus HTW Berlin Visual Comp Grp Berlin Germany

ISBN: (纸本)9781728118178

One of the key challenges of deep learning based image retrieval remains in aggregating convolutional activations into one highly representative feature vector. Ideally, this descriptor should encode semantic, spatial and low level information. Even though off-the-shelf pre-trained neural networks can already produce good representations in combination with aggregation methods, appropriate fine tuning for the task of image retrieval has shown to significantly boost retrieval performance. In this paper we present a simple yet effective supervised aggregation method built on top of existing regional pooling approaches. In addition to the maximum activation of a given region, we calculate regional average activations of extracted feature maps. Subsequently, weights for each of the pooled feature vectors are learned to perform a weighted aggregation to a single feature vector. Furthermore, we apply our newly proposed NRA loss function for deep metric learning to fine tune the backbone neural network and to learn the aggregation weights. Our method achieves state-of-the-art results for the INRIA Holidays data set and competitive results for the Oxford Buildings and Paris data sets while reducing the training time significantly.

关键词： computational and artificial intelligence Multi-layer neural network Image retrieval Content-based retrieval Machine learning Feature extraction Machine learning algorithms Nearest neighbor searches Computer vision

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Proceedings of the 2007 ieee symposium on computational intelligence in Image and signal processing, CIISP 2007

Proceedings of the 2007 IEEE Symposium on Computational Inte...

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2007 ieee symposium on computational intelligence in Image and signal processing, CIISP 2007

ISBN: (纸本)1424407079

The proceedings contain 76 papers. The topics discussed include: a new vehicle detection approach in traffic jam conditions;non-pixel robot stereo;a novel method to recognize complex dynamic gesture by combining HMM and FNN models;boundary refined texture segmentation based on K-views and datagram methods;single-row superposition-type spherical compound-like eye for pan-tilt motion recovery;bare bones strategy for human detection and tracking;Daubechies complex wavelet transform based moving object tracking;identification of dynamic nonlinear systems using computational intelligence techniques;a new invariant descriptor for shape representation and recognition;a wavelet-fuzzy logic based system to detect and identify electric disturbs;evolution strategies based particle filters for fault detection;and a multi-window stereo vision algorithm with improved performance at object borders.

关键词： Tracking (position)

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Tutorial CIMSVP-T advanced image processing

Tutorial CIMSVP-T advanced image processing

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ieee symposium on computational intelligence for multimedia signal and vision processing, CIMSVP

作者： Khan M. Iftekharuddin Department of Electrical and Computer Engineering University of Memphis Memphis USA

In this tutorial we discuss a number of basic concepts such as time and frequency domain image processing as well as advanced topics such as wavelets and image reconstruction. We also hope to demonstrate a few image p...

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An image processing based visual compensation system for vision defects

An image processing based visual compensation system for vis...

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IIH-MSP 2009 - 2009 5th International Conference on Intelligent Information Hiding and multimedia signal processing

作者： Lai, Chin-Lun Chang, Shu-Wen Communication Engineering Department Oriental Institute of Technology Taipei Taiwan Ophthalmology Department Far Eastern Memorial Hospital Taipei Taiwan

ISBN: (纸本)9780769537627

This paper is dedicated to develop an integrated portable aiding system for the visually impaired, such as color blindness, low vision, or visual field defects. First, individual visual model, including the effective visual field, color response, and contrast sensitivity, for each user can be evaluated by the proposed test method first. Then the input video sequence can be adjusted accordingly to fit each user's visual model hence to compensate their perceptual defects. In combination with head mounted micro displays, it is shown that the proposed visual auxiliary system can improve their visual awareness of the surroundings and enhance their visual perception effectively. © 2009 ieee.

关键词： Testing

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