Preface Introduction: The Role of the Reader I. Open 1. The Poetics of the Open Work 2. The Semantics of Metaphor 3. On the Possibility of Generating Aesthetic Messages in an Edenic Language II. Closed 4. The Myth of Superman 5. Rhetoric and Ideology in Sue's Les Mysteres de Paris 6. Narrative Structures in Fleming III. Open/Closed 7. Peirce and the Semiotic Foundations of Openness: Signs as Texts and Texts as Signs 8. Lector in Fabula: Pragmatic Strategy in a Metanarrative Text Appendix 1 Appendix 2 Bibliography

The Role of the Reader: Explorations in the Semiotics of Texts

Story and Discourse. Narrative Structure in Fiction and Film

This paper describes a technique for segmenting video using hidden Markov models (HMM). Video is segmented into regions defined by shots, shot boundaries, and camera movement within shots. Features for segmentation include an image-based distance between adjacent video frames, an audio distance based on the acoustic difference in intervals just before and after the frames, and an estimate of motion between the two frames. Typical video segmentation algorithms classify shot boundaries by computing an image-based distance between adjacent frames and comparing this distance to fixed, manually determined thresholds. Motion and audio information is used separately. In contrast, our segmentation technique allows features to be combined within the HMM framework. Further, thresholds are not required since automatically trained HMMs take their place. This algorithm has been tested on a video data base, and has been shown to improve the accuracy of video segmentation over standard threshold-based systems.

http://www.cse.psu.edu/~rtc12/CSE586Spring2010/papers/hmmvidseg.pdf

A hidden Markov model framework for video segmentation using audio and image features

A media browser, graphical user interface and method for browsing a media file wherein a user selects at least one feature in a media file and is provided with information regarding the existence of the selected feature in the media file. Based on the information, the user can identify and playback portions of interest in a media file. Features in a media file, such as a speaker's identity, applause, silence, motion, or video cuts, are preferably automatically time-wise evaluated in the media file using known methods. Metadata generated based on the time-wise feature evaluation are preferably mapped to confidence score values that represent a probability of a corresponding feature's existence in the media file. Confidence score information is preferably presented graphically to a user as part of a graphical user interface, and is used to interactively browse the media file.

Media browser using multimodal analysis

The system of the present invention allows a user to generate a representation of time-based media. The system of the present invention includes a feature extraction module for extracting features from media content. For example, the feature extraction module can detect solos in a musical performance, or can detect music, applause, speech, and the like. A formatting module formats a media representation generated by the system. The formatting module also applies feature extraction information to the representation, and formats the representation according to a representation specification. In addition, the system can include an augmented output device that generates a media representation based on the feature extraction information and the representation specification. The methods of the present invention include extracting features from media content, and formatting a media representation being generated using the extracted features and based on a specification or data structure specifying the representation format. The methods can also include generating a media representation based on the results of the formatting.

Printable representations for time-based media

Describes a method for the indexing and retrieval of multimedia data based on annotation and segmentation. Our goal is the retrieval of segments of audio and video that are suitable for inclusion in multimedia documents. Annotation refers to the association of text data with particular time locations of the media. Segmentation is the partitioning of continuous media into homogenous regions. Retrieval is performed over segments of the media using the annotations associated with the segments. We present two scenarios that describe how these techniques might be applied. In the first, we describe how excerpts from a video-taped usage study of a new device are located for inclusion in a report on the utility of the device. In the second, we show how sound bites from a recorded meeting are obtained for use in authoring a summary of the meeting.

Annotation and segmentation for multimedia indexing and retrieval

Because a hypermedia document is more complex than conventional text, it requires preparation with respect to two key aspects. First, the author begins to develop a "vision" of the document-usually based on some outline level description of his objectives. At the same time as this outline is being developed, the author begins to extract useful segments from his resource materials and prepares his first version of the logic of a system of hyperlinks among those segments. We present a system named "Authoring Environment for the Desktop" (AESOP) with two different types of "outlining" tools to handle these aspects. Planning the "vision" consists in defining a "logical" tree structure of the document. The plan for the link structure is based on a primitive unit called the view area, and AESOP provides a construct named Bento-Box for crating and manipulating view areas. Authors specify spatial and temporal layout within a single Bento-Box and define hyperlinks among the Bento-Boxes.

/pdf/aesop-an-outline-oriented-authoring-system-2koaz8cbf6.pdf

J. Boreczky

Papers

Annotation and segmentation for multimedia indexing and retrieval

AESOP: an outline-oriented authoring system