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Conference on Multimedia storage and Archiving Systems iv

作者： Durand, G Thienot, C Faudemay, P Univ Paris 06 Lab Informat Paris 6 F-75252 Paris 05 France

ISBN: (纸本)0819434396

An effective analysis of Visual Objects appearing in still images and video flames is required in order to offer fine grain access to multimedia and audiovisual contents. In previous papers, we showed how our method for segmenting still images into visual objects could improve content-based image retrieval and video analysis methods. Visual Objects are used in particular for extracting semantic knowledge about the contents. However, low-level segmentation methods for still images are not likely to extract a complex object as a whole but instead as a set of several sub-objects. For example, a person would be segmented into three visual objects: a face, hair, and a body. In this paper, we introduce the concept of Composite Visual Object. Such an object is hierarchically composed of sub-objects called Component Objects. Production rules implementing some common sense knowledge are used to extract and label composite visual objects based on the output of our still image segmentation method, and to label the component objects with their semantic values. Composite visual objects of the database (e.g.: "persons") can then be searched for, possibly with some constraints on some of their components (e.g.: "only with a blue suit!").

关键词： composite visual objects visual object extraction image segmentation multimedia content analysis MPEG-4 MPEG-7

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Event-Based Microservices With Apache Kafka Streams: A Real-Time Vehicle Detection System Based on Type, Color, and Speed Attributes

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IEEE ACCESS 2021年 9卷 83137-83148页

作者： Kul, Seda Tashiev, Isabek Sentas, Ali Sayar, Ahmet Kocaeli Univ Dept Comp Engn TR-41001 Kocaeli Turkey

The work presented in this paper proposes a novel approach to tracking a specific vehicle over the video streams published by the collaborating traffic surveillance cameras. In recent years, smart, effective transportation systems and intelligent traffic management applications are among the topics that have been given importance by various institutions. Developing a scalable, fault-tolerant, and resilient traffic monitoring system that retrieves video chunks with the desired query is challenging. For these challenging problems, stream processing and data retrieval systems have been developed over the years. However, there are still existing shortcomings between users and retrieval systems. This paper investigates the problem of retrieving video chunks by key-value query based on publish/subscribe model. Thus, we propose a hybrid of an asynchronous and synchronous communication mechanism for the Event-Based Microservice framework. We aim to develop generic techniques for better utilization of existing platforms. In the proposed framework, (i) first of all, microservices detect vehicles and extract their type, color, and speed features, and stored them in the metadata repository. (ii) Microservices publish each feature as events (iii) Other microservices self-join subscribe to those events, which leads to more events being published by combing all the possibilities: type-color, type-speed, color-speed, and type-color-speed. Finally, (iv) the system visualizes the query result and system status in real-time. When the user has selected color or/and a type or/and a speed feature, the system will return the best-matched vehicles without re-processing the videos. Experimental results show that our proposed system filters messages in real-time and supports easy integration of new microservices with the existing system.

关键词： Streaming media image color analysis Real-time systems databases Feature extraction Support vector machines Publish-subscribe Intelligent transportation system (ITS) microservices publish-subscribe system stream computing vehicle detection

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A comprehensive progressive decoding for JPEG compressed image

A comprehensive progressive decoding for JPEG compressed ima...

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Conference on storage and retrieval for Media databases 2003

作者： Feng, GC Baharudin, B Jiang, JM Univ Bradford Sch Informat EIMC Bradford BD7 1DP W Yorkshire England

ISBN: (纸本)0819448214

The explosive growth of images and videos on the World Wide Web (WWW) is making the Web into a huge resource of visual information. Among various types of multimedia information, still images or dynamic images (video clips) in compressed format are the most widely accepted on the WWW. Therefore, it becomes an essential issue to achieve the maximum efficiency in transmitting and decoding those compressed images on the Internet. Progressive coding provides a mode that allows a coarse version of an image being transmitted at a lower bit rate and then gradually refined by subsequent transmissions. Compared with conventional coding, it is more suitable for interactive applications such as those involving JPEG images on the Internet. In this paper, we first give an approximation of cosine function used in IDCT for the various orders. Based on the approximation and a series analysis, we then develop a progressive decoding scheme which comprehends the successive approximation and the spectral selection. The analysis and experiments establish the fact that our proposed method saves computational cost significantly in comparison with the existing spectral selection based progressive decoding proposed by JPEG. Extensive experiments are carried out to evaluate the proposed algorithm, which reveals that, the reconstructed images, even at the lowest bit rate and with lower order approximation, can still achieve encouraging PSNR values.

关键词： progressive coding JPEG compressed image successive approximation and spectral selection

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Comparison of automatic shot boundary detection algorithms

Comparison of automatic shot boundary detection algorithms

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7th storage and retrieval for image and video databases Conference

作者： Lienhart, R Intel Corp Microcomp Res Labs Santa Clara CA 95052 USA

ISBN: (纸本)0819431273

Various methods of automatic shot boundary detection have been proposed and claimed to perform reliably. Although the detection of edits is fundamental to any kind of video analysis since it segments a video into its basic components, the shots, only few comparative investigations on early shot boundary detection algorithms have been published. These investigations mainly concentrate on measuring the Edit detection performance, however;do not consider the algorithms' ability to classify the types and to locate the boundaries of the edits correctly. This gaper extends these comparative investigations More recent algorithms designed explicitly to detect specific complex editing operations such as fades and dissolves are taken into account and their ability to classify the types and locate the boundaries of such edits are examined. The algorithms' performance is measured in terms of hit rate, number of false hits, and miss rate for hard cuts, fades, and dissolves over a large and diverse set of video sequences. The experiments show, that while hard cuts and fades can be detected reliably, dissolves are still an open research issue The fate hit rate for dissolves is usually unacceptably high, ranging from 50% up to over 400%. Moreover;all algorithms seem to fail under roughly the same conditions.

关键词： video content analysis shot boundary detection hard cut detection fade detection dissolve detection

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Visual computing meets data modeling: defining objects in multicamera video databases

Visual computing meets data modeling: defining objects in mu...

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storage and retrieval for still image and video databases iv

作者： Kelly, Patrick H. Gupta, Amarnath Jain, Ramesh C. Univ. of California/San Diego La Jolla CA USA

ISBN: (纸本)0819420441

To the end-user of a video database, content consists of objects and events occurring in the video. A video database system must be designed to extract, represent and organize this information in a fashion that supports querying, manipulation and data visualization by a user. As a data modeling exercise, objects and events are defined in terms of semantic attributes such that an end-user's queries are expressible through the modeling language. On the other hand, as a feature extraction exercise, objects are defined as solutions to equations, often in terms of low-level visual primitives like voxels or contours. These two formalisms constitute entirely different languages. However, integration of these two approaches can provide a powerful mechanism for description and manipulation of complex visual data. This paper explores issues involved with this integration. We introduce the notion of a visual data modeling language (VDML), which supports data definition and data manipulation operations over complex visual data characteristic of video database systems. We discuss this data- modeling effort in the context of our multiple perspective interactive video system which generates three-dimensional data sets using input from multiple video cameras.

关键词： Database systems

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Direct feature extraction from compressed images

Direct feature extraction from compressed images

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storage and retrieval for still image and video databases iv

作者： Shen, Bo Sethi, Ishwar K. Wayne State Univ. Detroit MI USA

ISBN: (纸本)0819420441

This paper examines the issue of direct extraction of low level features from compressed images. Specifically, we consider the detection of areas of interest and edges in images compressed using the discrete cosine transform (DCT). For interest areas, we show how a measure based on certain DCT coefficients of a block can provide an indication of underlying activity. For edges, we show using an ideal edge model how the relative values of different DCT coefficients of a block can be used to estimate the strength and orientation of an edge. Our experimental results indicate that coarse edge information from compressed images can be extracted up to 20 times faster than conventional edge detectors.

关键词： image processing

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Indexing and retrieval of multimedia objects at different levels of granularity

Indexing and retrieval of multimedia objects at different le...

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Conference on Multimedia storage and Archiving Systems III

作者： Faudemay, P Durand, G Seyrat, C Tondre, N Univ Paris 06 LIP6 F-75255 Paris 05 France

ISBN: (纸本)0819429880

Intelligent access to multimedia databases for "naive user" should probably be based on queries formulation by "intelligent agents". These agents should "understand" the semantics of the contents, learn user preferences and deliver to the user a subset of the source contents, while keeping the freedom of choice of the user. Such systems should interpret multimedia contents in terms of multiple audiovisual objects (from video to visual or audio object), and on actions and scenarios. In our project we have developed a method for image segmentation into semantic objects, even in the case of still images. We use this method, and user-defined collections of such objects, and to characterize stories contents. For this purpose, we also use audio information from selected parts of the video. Stories are characterized by a set of visual concepts and words, and semantic similarity between stories is evaluated based on information retrieval methods. The system learns user preferences, and incrementally builds a user profile, which is used to present relevant stories in appropriate order. This approach was used to build a mockup of a simple "plus" engine, which is presently being experimented.

关键词： multimedia indexing video analysis spatial segmentation temporal segmentation example-based retrieval

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Model-based classification of visual information for content-based retrieval

Model-based classification of visual information for content...

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Proceedings of the 1999 7th Conference of the storage and retrieval for image and video databases VII

作者： Jaimes, Alejandro Chang, Shih-Fu Columbia Univ New York NY United States

A different approach to content-based retrieval and a novel framework for classification of visual information are proposed. The Visual Apprentice which is an implementation of the framework for still images and video that uses a combination of lazy-learning, decision trees, and evolution programs for classification and grouping is introduced. Examples and results are given to demonstrate the applicability of the proposed approach to perform visual classification and detection.

关键词： Feature extraction

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Interactive classification and indexing of still and motion pictures in videoRoadMap

Interactive classification and indexing of still and motion ...

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Conference on Multimedia storage and Archiving Systems III

作者： Park, YC Golshani, F Panchanathan, S Candan, KS Arizona State Univ Dept Comp Sci & Engn Tempe AZ 85287 USA

ISBN: (纸本)0819429880

The large scale proliferation of multimedia data necessitates the use of sophisticated techniques for accessing the information based on the content. videoRoadMap is a new content-based video indexing system for retrieving video clips and images from multimedia databases. The system indexes the audio-visual information using spatio-temporal features and information modeling methods. The proposed system employs adaptive similarity measurements based on the contents of media objects, resulting in more accurate retrievals. Principal component analysis and second order statistical analysis are employed to determine the appropriate combination of weight values in similarity search. In addition, videoRoadMap includes a powerful multi-faceted querying mechanism which allows queries to be formulated and presented in a variety of modes, including query by example (image and/or video), query by sketch, and query by object motion trajectory.

关键词： content-based multimedia object retrieval subjectivity modeling audio-visual information analysis

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ClickPoints: an expandable toolbox for scientific image annotation and analysis

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METHODS IN ECOLOGY AND EVOLUTION 2017年第6期8卷 750-756页

作者： Gerum, Richard C. Richter, Sebastian Fabry, Ben Zitterbart, Daniel P. Univ Erlangen Nurnberg BioPhys Grp Erlangen Germany Woods Hole Oceanog Inst Appl Ocean Phys & Engn Woods Hole MA 02543 USA Helmholtz Ctr Polar & Marine Res Alfred Wegener Inst Bremerhaven Germany

1. Optical recordings are ubiquitous in current scientific research. As recording and storing images and videos have become simpler and cheaper over the past years, new and more efficient tools are needed to analyse the growing amount of data. While current scientific image analysis tools focus on medical 3D data sets, a tool for efficiently handling large-scale 2D time-series recordings is still missing. 2. We developed Click Points, an expandable, open-source, Python-based software to fill this gap. ClickPoints combines and streamlines the three main steps of image analysis - visualization, annotation and evaluation - in one program. 3. ClickPoints enables the user to (i) efficiently review large data sets of images and videos, (ii) annotate interesting findings and (iii) facilitate manual and automatic evaluations. ClickPoints is highly versatile, ranging from clicking and selecting objects with simple markers, drawing masks and computing trajectories, up to (iv) custom-written Python add-ons for adapting or extending the available features. These add-ons (v) reduce development time by utilizing Click Points' display, interface and storage solutions. In addition, ClickPoints provides an (vi) extensive data base application programming interface to facilitate efficient storage and retrieval of results. 4. ClickPoints is designed to simplify repetitive and labour-intensive scientific tasks, especially when dealing with large image and video time-series recordings. ClickPoints offers cross-platform support for Windows and Linux and is released under the GPLv3 license. Download, documentation and numerous examples are available at http://***.

关键词： ground truth image annotation image evaluation labelling open source Python time-series data visual data processing

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