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Candela-storage, Analysis and retrieval of video Content in Distributed Systems: Real-Time video Surveillance and retrieval

Candela-Storage, Analysis and Retrieval of Video Content in ...

引用

IEEE International conference on Multimedia and Expo (ICME)

作者： E.G.T. Jaspers R.G.J. Wijnhoven A.H.R. Albers X. Desurmont M. Barais J. Hamaide B. Lienard Bosch Security Systems Netherlands Multitel Parc Initialis Mons Belgium Vrije Universiteit Brussel Brussels Belgium

Although many different types of technologies for information systems have evolved over the last decades (such as databases, video systems, the Internet and mobile telecommunication), the integration of these technologies is just in its infancy and has the potential to introduce "intelligent" systems. This paper describes the novelties of a video content analysis in a surveillance system, demonstrating the benefits for fast retrieval in huge video databases

关键词： Content based retrieval Real time systems video surveillance databases Algorithm design and analysis image analysis Data security Information security Information retrieval Computer vision

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Design and Implementation of Distributed video retrieval System in Air Monitoring Warning System

Design and Implementation of Distributed Video Retrieval Sys...

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International conference on Measuring Technology and Mechatronics Automation, ICMTMA

作者： Chen Na Zhu Ya Ling College of Software Engineering Lanzhou Institute of Technology Lanzhou China

ISBN: (纸本)9781467371445

The video monitoring system plays a decisive role on the security of the sensitive areas, the video will be recording when the system monitors a warning behavior, accumulating over a long period, which will produce a large amount of video information, It is becoming crucial that how to retrieve these massive video information effectively and efficiently. The Content-based video retrieval technology has been the research hotspots in recent years. This paper, with the mature technology of video key frame extraction, combining with the SIFT feature extraction and matching, as well as LSH mapping, realizes the video retrieval. During the process of feature extraction and matching to the video key frame, we realize the distributed processing and storage, using MapReduce parallel mode and HBase distributed storage system, which is the application development of the Content-based video retrieval on the parallel analysis and scalable storage.

关键词： Monitoring Feature extraction Indexes Distributed databases Streaming media image retrieval Distributed processing

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Multimedia databases

Multimedia databases

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International conference on Information Visualisation (IV)

作者： O. Kalipsiz Computer Science Department Yildiz Technical University Istanbul Turkey

A multimedia database is a controlled collection of multimedia data items such as text, images, graphic objects, video and audio. A multimedia database management system (DBMS) provides support for the creation, storage, access, querying and control of a multimedia database. The requirements of a multimedia DBMS are: multimedia data modeling; multimedia object storage; multimedia indexing, retrieval and browsing; and multimedia query support. This paper discusses a general framework for multimedia database systems and describes the requirements and architecture for these systems.

关键词： Multimedia databases Multimedia systems Database systems Graphics Animation video compression image databases Indexing Information retrieval videoconference

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Distributional clustering for efficient content-based retrieval of images and video

Distributional clustering for efficient content-based retrie...

引用

IEEE International conference on image Processing

作者： G. Iyengar A.B. Lippman IBM Thomas J. Watson Research Center Yorktown Heights NY USA MIT Media Laboratory Cambridge MA USA

ISBN: (纸本)0780362977

We present an approach to clustering images for efficient retrieval using relative entropy. We start with the assumption that visual features are represented by probability densities and develop clustering algorithms for probability densities (for example, normalized histograms are crude approximations of probability densities). These clustering algorithms are then used for efficient retrieval of images and video.

关键词： image retrieval Content based retrieval image databases Clustering algorithms Histograms image storage Partitioning algorithms Laboratories Entropy Data security

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image indexing using composite regional color channels features

Image indexing using composite regional color channels featu...

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Proceedings of the 1999 7th conference of the storage and retrieval for image and video databases Vii

作者： Appas, Ahmed R. Darwish, Ahmed M. El-Desouki, Ayman I. Shaheen, Samir I. Electronic Research Inst Dokki Egypt

Color indexing is a technique by which images in the database could be retrieved on the bases of their color content. In this paper, we propose a new set of color features for representing color images, and show how they can be computed and used efficiently to retrieve images that possess certain similarity. These features are based on the first three moments of each color channel. Two differences distinguish this work from previous work reported in the literature. First, we compute the third moment of the color channel distribution around the second moment not around the first moment. The second moment is less sensitive to small luminance changes, than the first moment. Second we combine all three moment values in a single descriptor. This reduces the number of floating point values needed to index the image and hence speeds up the search. To give the user flexibility in terms of defining his center of attention during query time, the proposed approach divides the image into five geometrical regions and allows the user to give different weights for each region to designate its importance. The approach has been tested on databases of 205 images of airplanes and natural scenes. It proved to be insensitive to small rotations and small translations in the image and yielded a better hit rate than similar algorithms previously reported in the literature.

关键词： image analysis

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Synthetic summaries of video sequences using a multiresolution based key frame selection technique in a perceptually uniform color space

Synthetic summaries of video sequences using a multiresoluti...

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IEEE International conference on image Processing

作者： P. Campisi A. Neri Dipartimento Ingegneria Elettronica Università degli Studi di Roma Roma Tre Rome Italy

video databases are very demanding systems as far as mass storage requirements and computational resources necessary to perform common database operations, such as browsing and retrieval, are required. These operations can be simplified both in terms of the computational complexity and of processing time by performing them on an ensemble of frames, called key frames, representative of the content units (shots) in which a video can be segmented. An adaptive key frames extraction method based on a wavelet based multiresolution analysis in a perceptually uniform color space is presented. Experimental results that show the effectiveness of the proposed technique to select key frames summarizing the video's content, are finally provided.

关键词： video sequences Data mining Color Sampling methods Information retrieval Multiresolution analysis Multimedia databases Wavelet analysis Software libraries Computational complexity

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EFFICIENT video SEARCH USING image QUERIES

EFFICIENT VIDEO SEARCH USING IMAGE QUERIES

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IEEE International conference on image Processing

作者： A. Araujo M. Makar V. Chandrasekhar D. Chen S. Tsai H. Chen R. Angst B. Girod Stanford University Qualcomm Inc. Institute for Infocomm Research

ISBN: (纸本)9781479957521

We study the challenges of image-based retrieval when the database consists of videos. This variation of visual search is important for a broad range of applications that require indexing video databases based on their visual contents. We present new solutions to reduce storage requirements, while at the same time improving video search quality. The video database is preprocessed to find different appearances of the same visual elements, and build robust descriptors. Compression algorithms are developed to reduce system's storage requirements. We introduce a dataset of CNN broadcasts and queries that include photos taken with mobile phones and images of objects. Our experiments include pairwise matching and retrieval scenarios. We demonstrate one order of magnitude storage reduction and search quality improvements of up to 12% in mean average precision, compared to a baseline system that does not make use of our techniques.

关键词： Efficient video search image-based retrieval

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Smart search & retrieval on video databases

Smart search & retrieval on video databases

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IEEE International conference on Consumer Electronics (ICCE)

作者： A.H.R. Albers R.G.J. Wijnhoven E.G.T. Jaspers P.H.N. de With Eindhovan University of Technology Eindhoven Netherlands Logica-CMG Eindhoven Netherlands

A system for fast searching in video databases is proposed, exploiting the location data of tracking algorithms. A key advantage is the sampling of object behavior independent of the frame rate, resulting in a very efficient storage. Results show that the search time on large video data sets significantly reduces, compared to traditional methods

关键词： Information retrieval video compression video surveillance image databases Filtering algorithms Data security Sampling methods Bit rate Content management Indexing

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image retrieval in Multimedia databases: A Survey

Image Retrieval in Multimedia Databases: A Survey

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International conference on Intelligent Information Hiding and Multimedia Signal Processing (iiHMSP)

作者： Yihun Alemu Jong-bin Koh Muhammed Ikram Dong-Kyoo Kim Department of Computer Engineering Ajou University Suwon South Korea

In the past decades the advancement in the area of database management systems shifts towards multimedia. Multimedia information is very expressive, self explanatory, narrative, etc. Now a day the development of digital media, advanced network infrastructure and the easily available consumer electronics makes the multimedia revolution to run in an alarming rate. Inline with the advancement of database technology that incorporates multimedia data, an open question that always rose in the technology is how to retrieve/search images in the multimedia databases. There are a huge number of research works focusing on the searching mechanisms in image databases for efficient retrieval and tried to give supplementary suggestions on the overall systems. The growing of digital medias (digital camera, digital video, digital TV, e-book, cell phones, etc.) gave rise to the revolution of very large multimedia databases, in which the need of efficient storage, organization and retrieval of multimedia contents came into question. Among the multimedia data, this survey paper focuses on the different methods (approaches) and their evaluation techniques used by many of recent research works on image retrieval system. Many researchers develop and use lots of approaches towards image retrieval. This paper, in general, classified image retrieval into text based and content based, including the newly growing ontology based image retrieval system as one focus. We address, in this paper, the challenges, techniques and evaluation methods used in image retrieval systems through a detailed look of most recent works.

关键词： Information retrieval image retrieval Multimedia databases Multimedia systems Content based retrieval image databases Database systems Consumer electronics Digital cameras Digital TV

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Piecewise Hashing: A Deep Hashing Method for Large-Scale Fine-Grained Search 3rd

Piecewise Hashing: A Deep Hashing Method for Large-Scale Fin...

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3rd Chinese conference on Pattern Recognition and Computer Vision (PRCV)

作者： Wang, Yimu Wei, Xiu-Shen Xue, Bo Zhang, Lijun Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China Nanjing Univ Sci & Technol Minist Educ PCA Lab Key Lab Intelligent Percept & Syst High Dimens In Nanjing Peoples R China Nanjing Univ Sci & Technol Jiangsu Key Lab Image & Video Understanding Socia Sch Comp Sci & Engn Nanjing Peoples R China

ISBN: (纸本)9783030606381;9783030606398

Fine-grained search task such as retrieving subordinate categories of birds, dogs or cars, has been an important but challenging problem in computer vision. Although many effective fine-grained search methods were developed, with the amount of data increasing, previous methods fail to handle the explosive fine-grained data with low storage cost and fast query speed. On the other side, since hashing sheds its light in large-scale image search for dramatically reducing the storage cost and achieving a constant or sub-linear time complexity, we leverage the power of hashing techniques to tackle this valuable yet challenging vision task, termed as fine-grained hashing in this paper. Specifically, our proposed method consists of two crucial modules, i.e., the bilinear feature learning and the binary hash code learning. While the former encodes both local and global discriminative information of a fine-grained image, the latter drives the whole network to learn the final binary hash code to present that fine-grained image. Furthermore, we also introduce a novel multi-task hash training strategy, which can learn hash codes of different lengths simultaneously. It not only accelerates training procedures, but also significantly improves the fine-grained search accuracy. By conducting comprehensive experiments on diverse fine-grained datasets, we validate that the proposed method achieves superior performance over the competing baselines.

关键词： Fine-grained image retrieval Deep hashing Multi-task learning Large-scale methods

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