Browsing by Subject "MPEG-4"

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    ItemOpen 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.
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    Scene representation technologies for 3DTV-a survey
    (Institute of Electrical and Electronics Engineers, 2007-11) Alatan, A. A.; Yemez, Y.; Güdükbay, Uğur; Zabulis, X.; Müller, K.; Erdem, C.; Weigel, C.; Smolic, A.
    3-D scene representation is utilized during scene extraction, modeling, transmission and display stages of a 3DTV framework. To this end, different representation technologies are proposed to fulfill the requirements of 3DTV paradigm. Dense point-based methods are appropriate for free-view 3DTV applications, since they can generate novel views easily. As surface representations, polygonal meshes are quite popular due to their generality and current hardware support. Unfortunately, there is no inherent smoothness in their description and the resulting renderings may contain unrealistic artifacts. NURBS surfaces have embedded smoothness and efficient tools for editing and animation, but they are more suitable for synthetic content. Smooth subdivision surfaces, which offer a good compromise between polygonal meshes and NURBS surfaces, require sophisticated geometry modeling tools and are usually difficult to obtain. One recent trend in surface representation is point-based modeling which can meet most of the requirements of 3DTV, however the relevant state-of-the-art is not yet mature enough. On the other hand, volumetric representations encapsulate neighborhood information that is useful for the reconstruction of surfaces with their parallel implementations for multiview stereo algorithms. Apart from the representation of 3-D structure by different primitives, texturing of scenes is also essential for a realistic scene rendering. Image-based rendering techniques directly render novel views of a scene from the acquired images, since they do not require any explicit geometry or texture representation. 3-D human face and body modeling facilitate the realistic animation and rendering of human figures that is quite crucial for 3DTV that might demand real-time animation of human bodies. Physically based modeling and animation techniques produce impressive results, thus have potential for use in a 3DTV framework for modeling and animating dynamic scenes. As a concluding remark, it can be argued that 3-D scene and texture representation techniques are mature enough to serve and fulfill the requirements of 3-D extraction, transmission and display sides in a 3DTV scenario. © 2007 IEEE.
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    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.
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    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.
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    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.