211 research outputs found

    Determination of Mechanical Properties of Concrete by Destructive and Non-Destructive Experimental Methods

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    This paper examines the mechanical quality differences of concrete by destructive and non destructive methods according to shape, dimension relationship and cure conditions. Within destructive methods, (compression, tension, bending) different shaped-sized concretes and 28-days-old concrete shear wall samples tested along to find modulus of elasticity. Non destructive methods (ultrasonic pulse velocity test, rebound hammer test) applied same samples along to determine compressive strength and longitudinal wave velocity to obtain result of modulus of elasticity. The aim was to achieve data from applied laboratory test results and cross-checking, all values to enhance concretes compressive strength for potential possibilities

    Scenario-Based Query Processing for Video-Surveillance Archives

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    Cataloged from PDF version of article.Automated video surveillance has emerged as a trendy application domain in recent years, and accessing the semantic content of surveillance video has become a challenging research area. The results of a considerable amount of research dealing with automated access to video surveillance have appeared in the literature; however, significant semantic gaps in event models and content-based access to surveillance video remain. In this paper, we propose a scenario-based query-processing system for video surveillance archives. In our system, a scenario is specified as a sequence of event predicates that can be enriched with object-based low-level features and directional predicates. We introduce an inverted tracking scheme, which effectively tracks the moving objects and enables view-based addressing of the scene. Our query-processing system also supports inverse querying and view-based querying, for after-the-fact activity analysis. We propose a specific surveillance query language to express the supported query types in a scenario-based manner. We also present a visual query-specification interface devised to facilitate the query-specification process. We have conducted performance experiments to show that our query-processing technique has a high expressive power and satisfactory retrieval accuracy in video surveillance. (C) 2009 Elsevier Ltd. All rights reserved

    A histogram-based approach for object-based query-by-shape-and-color in image and video databases

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    Cataloged from PDF version of article.Considering the fact that querying by low-level object features is essential in image and video data, an efficient approach for querying and retrieval by shape and color is proposed. The approach employs three specialized histograms, (i.e. distance, angle, and color histograms) to store feature-based information that is extracted from objects. The objects can be extracted from images or video frames. The proposed histogram-based approach is used as a component in the query-by-feature subsystem of a video database management system. The color and shape information is handled together to enrich the querying capabilities for content-based retrieval. The evaluation of the retrieval effectiveness and the robustness of the proposed approach is presented via performance experiments. (C) 2005 Elsevier Ltd All rights reserved

    A rule-based video database system architecture

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    Cataloged from PDF version of article.We propose a novel architecture for a video database system incorporating both spatio-temporal and semantic (keyword, event/activity and category-based) query facilities. The originality of our approach stems from the fact that we intend to provide full support for spatio-temporal, relative object-motion and similarity-based objecttrajectory queries by a rule-based system utilizing a knowledge-base while using an object-relational database to answer semantic-based queries. Our method of extracting and modeling spatio-temporal relations is also a unique one such that we segment video clips into shots using spatial relationships between objects in video frames rather than applying a traditional scene detection algorithm. The technique we use is simple, yet novel and powerful in terms of effectiveness and user query satisfaction: video clips are segmented into shots whenever the current set of relations between objects changes and the video frames, where these changes occur, are chosen as keyframes. The directional, topological and third-dimension relations used for shots are those of the keyframes selected to represent the shots and this information is kept, along with frame numbers of the keyframes, in a knowledge-base as Prolog facts. The system has a comprehensive set of inference rules to reduce the number of facts stored in the knowledge-base because a considerable number of facts, which otherwise would have to be stored explicitly, can be derived by rules with some extra effort. (C)2002 Elsevier Science Inc. All rights reserved

    OBJECTIVE: a benchmark for object-oriented active database systems

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    Cataloged from PDF version of article.Although much work in the area of Active Database Management Systems (ADBMSs) has been done, it is not yet clear how the performance of an active DBMS can be evaluated systematically. In this paper, we describe the OBJECTIVE Benchmark for object-oriented ADBMSs, and present experimental results from its implementation in an active database system prototype. OBJECTIVE can be used to identify performance bottlenecks and active functionalities of an ADBMS, and to compare the performance of multiple ADBMSs. (C) 1999 Published by Elsevier Science Inc. All rights reserved

    Automatic detection of salient objects and spatial relations in videos for a video database system

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    Cataloged from PDF version of article.Multimedia databases have gained popularity due to rapidly growing quantities of multimedia data and the need to perform efficient indexing, retrieval and analysis of this data. One downside of multimedia databases is the necessity to process the data for feature extraction and labeling prior to storage and querying. Huge amount of data makes it impossible to complete this task manually. We propose a tool for the automatic detection and tracking of salient objects, and derivation of spatio-temporal relations between them in video. Our system aims to reduce the work for manual selection and labeling of objects significantly by detecting and tracking the salient objects, and hence, requiring to enter the label for each object only once within each shot instead of specifying the labels for each object in every frame they appear. This is also required as a first step in a fully-automatic video database management system in which the labeling should also be done automatically. The proposed framework covers a scalable architecture for video processing and stages of shot boundary detection, salient object detection and tracking, and knowledge-base construction for effective spatio-temporal object querying. (c) 2008 Elsevier B.V. All rights reserved

    Bilvideo-7: an MPEG-7- compatible video indexing and retrieval system

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    Cataloged from PDF version of article.BilVideo-7 is an MPEG-7-compatible, distributed, video indexing and retrieval system that supports complex multimodal queries in a unified framework

    BilVideo: A video database management system

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    Cataloged from PDF version of article.The BilVideo video database management system provides integrated support for spatiotemporal and semantic queries for video. BilVideo can support any application with video data searching needs. It's query language provides a simple way to extend the system's query capabilities. Users can add application-dependent rules and facts to the knowledge base

    An efficient query optimization strategy for spatio-temporal queries in video databases

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    Cataloged from PDF version of article.The interest for multimedia database management systems has grown rapidly due to the need for the storage of huge volumes of multimedia data in computer systems. An important building block of a multimedia database system is the query processor, and a query optimizer embedded to the query processor is needed to answer user queries efficiently. Query optimization problem has been widely studied for conventional database systems; however it is a new research area for multimedia database systems. Due to the differences in query processing strategies, query optimization techniques used in multimedia database systems are different from those used in traditional databases. In this paper, a query optimization strategy is proposed for processing spatio-temporal queries in video database systems. The proposed strategy includes reordering algorithms to be applied on query execution tree. The performance results obtained by testing the reordering algorithms on different query sets are also presented. (C) 2003 Elsevier Inc. All rights reserved

    HandVR: a hand-gesture-based interface to a video retrieval system

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    Cataloged from PDF version of article.Using one's hands in human-computer interaction increases both the effectiveness of computer usage and the speed of interaction. One way of accomplishing this goal is to utilize computer vision techniques to develop hand-gesture-based interfaces. A video database system is one application where a hand-gesture-based interface is useful, because it provides a way to specify certain queries more easily. We present a hand-gesture-based interface for a video database system to specify motion and spatiotemporal object queries. We use a regular, low-cost camera to monitor the movements and configurations of the user's hands and translate them to video queries. We conducted a user study to compare our gesture-based interface with a mouse-based interface on various types of video queries. The users evaluated the two interfaces in terms of different usability parameters, including the ease of learning, ease of use, ease of remembering (memory), naturalness, comfortable use, satisfaction, and enjoyment. The user study showed that querying video databases is a promising application area for hand-gesture-based interfaces, especially for queries involving motion and spatiotemporal relations. © 2014 Springer-Verlag London
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