Video object extraction and representation [[electronic resource] ] : theory and applications / / by I-Jong Lin, S.Y. Kung

• Record Nr.: UNINA9910817770403321
• Autore: Lin I-Jong <1971->
• Pubbl/distr/stampa: Boston, Mass., : Kluwer Academic Publisher, 2000
• ISBN: 1-280-20637-3; 9786610206377; 0-306-47037-3
• Edizione: [1st ed. 2002.]
• Descrizione fisica: 1 online resource (192 p.)
• Collana: The Kluwer international series in engineering and computer science ; ; SECS 584
• Altri autori (Persone): KungS. Y (Sun Yuan)
• Disciplina: 621.388/33
• Soggetti: Digital video; MPEG (Video coding standard); Image processing - Digital techniques; Directed graphs
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references (p. [163]-173) and index.
• Nota di contenuto: to Content-Based Visual Processing -- Existing Techniques of Visual Processing -- Voronoi Ordered Space -- A System for Video Object Segmentation -- Robust Representation of Shape with DAGs -- A System for Image/Video Object Query by Shape -- The Future of Content-Based Video Processing.
• Sommario/riassunto: “If you have built castles in the air, your work need not be lost; that is where they should be. Now put the foundations under them. ” - Henry David Thoreau, Walden Although engineering is a study entrenched firmly in belief of pr- matism, I have always believed its impact need not be limited to pr- matism. Pragmatism is not the boundaries that define engineering, just the (sometimes unforgiving) rules by which we sight our goals. This book studies two major problems of content-based video proce- ing for a media-based technology: Video Object Plane (VOP) Extr- tion and Representation, in support of the MPEG-4 and MPEG-7 video standards, respectively. After reviewing relevant image and video p- cessing techniques, we introduce the concept of Voronoi Ordered Spaces for both VOP extraction and representation to ; integrate shape infor- tion into low-level optimization algorithms and to derive robust shape descriptors, respectively. We implement a video object segmentation system with a novel surface optimization scheme that integrates Voronoi Ordered Spaces with existing techniques to balance visual information against predictions of models of a priori information. With these VOPs, we have explicit forms of video objects that give users the ability to - dress and manipulate video content. We outline a general methodology of robust data representation and comparison through the concept of complex partitioning mapped onto Directed Acyclic Graphs (DAGs).