Browsing by Subject "MPEG-7"

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Open Access
Bilvideo-7: an MPEG-7-compatible video indexing and retrieval system
(Institute of Electrical and Electronics Engineers, 2010-07) Baştan M.; Çam, H.; Güdükbay, Uğur; Ulusoy, Özgür
BilVideo-7 is an MPEG-7-compatible, distributed, video indexing and retrieval system that supports complex multimodal queries in a unified framework.
Open Access
Image sequence analysis for emerging interactive multimedia services-the European COST 211 framework
(Institute of Electrical and Electronics Engineers, 1998-11) Alatan, A. A.; Onural, L.; Wollborn, M.; Mech, R.; Tuncel, E.; Sikora, T.
Flexibility and efficiency of coding, content extraction, and content-based search are key research topics in the field of interactive multimedia. Ongoing ISO MPEG-4 and MPEG-7 activities are targeting standardization to facilitate such services. European COST Telecommunications activities provide a framework for research collaboration. COST 211 bis and COST 211 tcr activities have been instrumental in the definition and development of the ITU-T H.261 and H.263 standards for video-conferencing over ISDN and videophony over regular phone lines, respectively. The group has also contributed significantly to the ISO MPEG-4 activities. At present a significant effort of the COST 211 tcr group activities is dedicated toward image and video sequence analysis and segmentation - an important technological aspect for the success of emerging object-based MPEG-4 and MPEG-7 multimedia applications. The current work of COST 211 is centered around the test model, called the Analysis Model (AM). The essential feature of the AM is its ability to fuse information from different sources to achieve a high-quality object segmentation. The current information sources are the intermediate results from frame-based (still) color segmentation, motion vector based segmentation, and change-detection-based segmentation. Motion vectors, which form the basis for the motion vector based intermediate segmentation, are estimated from consecutive frames. A recursive shortest spanning tree (RSST) algorithm is used to obtain intermediate color and motion vector based segmentation results. A rule-based region processor fuses the intermediate results; a postprocessor further refines the final segmentation output. The results of the current AM are satisfactory; it is expected that there will be further improvements of the AM within the COST 211 project.
Open Access
Metadata extraction from text in soccer domain
(IEEE, 2008-10) Göktürk, Z. O.; Çiçekli, N. K.; Çiçekli, İlyas
Event detection is a crucial part for soccer video searching and querying. The event detection could be done by video content itself or from a structured or semi structured text files gathered from sports web sites. In this paper, we present an approach of metadata extraction from match reports for soccer domain. The UEFA Cup and UEFA Champions League Match Reports are downloaded from the web site of UEFA by a web-crawler. Using regular expressions we annotate these match reports and then extract events from annotated match reports. Extracted events are saved in an MPEG-7 file. We present an interface that is used to query the events in the MPEG-7 match corpus. If an associated match video is available, the video portions that correspond to the found events could be played. © 2008 IEEE.
Open Access
An MPEG-7 compatible video retrieval system with integrated support for complex multimodal queries
(IEEE Computer Society, 2019) Baştan, Muhammet; Çam, Hayati; Güdükbay, Uğur; Ulusoy, Özgür
We present BilVideo-7, an MPEG-7 compatible, video indexing and retrieval system that supports complex multimodal queries in a unified framework. An MPEG-7 profile is developed to represent the videos by decomposing them into Shots, Keyframes, Still Regions and Moving Regions. The MPEG-7 compatible XML representations of videos according to this profile are obtained by the MPEG-7 compatible video feature extraction and annotation tool of BilVideo-7, and stored in a native XML database. Users can formulate text-based semantic, color, texture, shape, location, motion and spatio-temporal queries on an intuitive, easy-to-use Visual Query Interface, whose Composite Query Interface can be used to specify very complex queries containing any type and number of video segments with their descriptors. The multi-threaded Query Processing Server parses incoming queries into subqueries and executes each subquery in a separate thread. Then, it fuses subquery results in a bottom-up manner to obtain the final query result. The whole system is unique in that it provides very powerful querying capabilities with a wide range of descriptors and multimodal query processing in an MPEG-7 compatible interoperable environment. We present sample queries to demonstrate the capabilities of the system.
Open Access
Query processing for an MPEG-7 compliant video database
(2008) Çam, Hayati
Based on the recent advancements in multimedia, communication, and storage technologies, the amount of audio-visual content stored is increased dramatically. The need to organize and access the growing multimedia content led researchers to develop multimedia database management systems. However, each system has its own way of describing the multimedia content that disables interoperability among other systems. To overcome this problem and to be able to standardize the description of audio-visual content stored in those databases, MPEG-7 standard has been developed by MPEG (Moving Picture Experts Group). In this thesis, a query language and a query processor for an MPEG-7 compliant video database system is proposed. The query processor consists of three main modules: query parsing module, query execution module, and result fusion module. The query parsing module parses the XML based query and divides it into subqueries. Each sub-query is then executed with related query execution module and the final result is obtained by fusing the results of the sub-queries according to user defined weights. The prototype video database system BilVideo v2.0, which is formed as a result of this thesis work, supports spatio-temporal and low level feature queries that contain any weighted combination of keyword, temporal, spatial, trajectory, and low level visual feature (color, shape and texture) queries. Compatibility with MPEG-7, low-level visual query support, and weighted result fusion feature are the major factors that highly differentiate between BilVideo v2.0 and its predecessor, BilVideo.
Open Access
Semi-automatic video object segmentation
(2000) Esen, Ersin
Content-based iunetionalities form the core of the future multimedia applications. The new multimedia standard MPEG-4 provides a new form of interactivity with coded audio-visual data. The emerging standard MPEG-7 specifies a common description of various types of multimedia information to index the data for storage and retrieval. However, none of these standards specifies how to extract the content of the multimedia data. Video object segmentation addresses this task and tries to extract semantic objects from a scene. Two tyj)es of video object segmentation can be identified: unsupervised and supervised. In unsupervised méthods the user is not involved in any step of the process. In supervised methods the user is requested to supply additional information to increase the quality of the segmentation. The proposed weakly supervised still image segmentation asks the user to draw a scribble over what he defines as an object. These scribbles inititate the iterative method. .A.t each iteration the most similar regions are merged until the desired numljer of regions is reached. The proposed .segmentation method is inserted into the unsupervised COST211ter .A-ualysis Model (.A.M) for video object segmentation. The AM is modified to handh' the sujiervision. The new semi-automatic AM requires the user intei actimi for onl>· first frame of the video, then segmentation and object tracking is doin' automatically. The results indicate that the new semi-automatic AM constituK's a good tool for video oliject segmentation.
Open Access
Utilization of improved recursive-shortest-spanning-tree method for video object segmentation
(1997) Tuncel, Ertem
Emerging standards MPEG-4 and MPEG-7 do not standardize the video object segmentation tools, although their performance depends on them. There are a lot of still image segmentation algorithms in the literature, like clustering, split-and-merge, region merging, etc. One of these methods, namely the recursive shortest spanning tree (RSST) method, is improved so that a still image is approximated as a piecewise planar function, and well-approximated areas on the image are extracted cis regions. A novel video object segmentation algorithm, which takes the previously estimated 2-D dense motion vector field as input, and uses this improved RSST method to approximate each component of the motion vector field as a piecewise planar function, is proposed. The algorithm is successful in locating 3-D planar objects in the scene correctly, with acceptable accuracy at the boundaries. Unlike the existing algorithms in the literature, the proposed algorithm is fast, parameter-free and requires no initial guess about the segmentation result. Moreover, it is a hierarchical scheme which gives finest to coarsest segmentation results. The proposed algorithm is inserted into the current version of the emerging “Analysis Model (AM)” of the Europan COST21U'’’ project, and it is observed that the current AM is outperformed.
Open Access
Video object segmentation for interactive multimedia
(1998) Ekmekçi, Tolga
Recently, trends in video processing research have shifted from video compression to video analysis, due to the emerging standards MPEG-4 and MPEG-7. These standards will enable the users to interact with the objects in the audiovisual scene generated at the user’s end. However, neither of them prescribes how to obtain the objects. Many methods have been proposed for segmentation of video objects. One of the approaches is the “Analysis Model” (AM) of European COST-211 project. It is a modular approach to video object segmentation problem. Although AM performs acceptably in some cases, the results in many other cases are not good enough to be considered as semantic objects. In this thesis, a new tool is integrated and some modules are replaced by improved versions. One of the tools uses a block-based motion estimation technique to analyze the motion content within a scene, computes a motion activity parameter, and skips frames accordingly. Also introduced is a powerful motion estimation method which uses maximum a posteriori probability (MAP) criterion and Gibbs energies to obtain more reliable motion vectors and to calculate temporally unpredictable areas. To handle more complex motion in the scene, the 2-D affine motion model is added to the motion segmentation module, which employs only the translational model. The observed results indicate that the AM performance is improved substantially. The objects in the scene and their boundaries are detected more accurately, compared to the previous results.