878 resultados para Motion pictures in agriculture
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This paper addresses the challenge of bridging the semantic gap between the rich meaning users desire when they query to locate and browse media and the shallowness of media descriptions that can be computed in today's content management systems. To facilitate high-level semantics-based content annotation and interpretation, we tackle the problem of automatic decomposition of motion pictures into meaningful story units, namely scenes. Since a scene is a complicated and subjective concept, we first propose guidelines from fill production to determine when a scene change occurs. We then investigate different rules and conventions followed as part of Fill Grammar that would guide and shape an algorithmic solution for determining a scene. Two different techniques using intershot analysis are proposed as solutions in this paper. In addition, we present different refinement mechanisms, such as film-punctuation detection founded on Film Grammar, to further improve the results. These refinement techniques demonstrate significant improvements in overall performance. Furthermore, we analyze errors in the context of film-production techniques, which offer useful insights into the limitations of our method.
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This paper presents an original computational approach to extraction of movie tempo for deriving story sections and events that convey high level semantics of stories portrayed in motion pictures, thus enabling better video annotation and interpretation systems. This approach, inspired by the existing cinematic conventions known as film grammar, uses the attributes of motion and shot length to define and compute a novel continuous measure of tempo of a movie. Tempo flow plots are derived for several full-length motion pictures and edge detection is performed to extract dramatic story sections and events occurring in the movie, underlined by their unique tempo. The results confirm reliable detection of actual distinct tempo changes and serve as useful index into the dramatic development and narration of the story in motion pictures.
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This work constitutes the first attempt to extract an important narrative structure, the 3-Act story telling paradigm, in film. This narrative structure is prevalent in the domain of film as it forms the foundation and framework in which the film can be made to function as an effective tool for story telling, and its extraction is a vital step in automatic content management for film data. A novel act boundary likelihood function for Act 1 is derived using a Bayesian formulation under guidance from film grammar, tested under many configurations and the results are reported for experiments involving 25 full length movies. The formulation is shown to be a useful tool in both the automatic and semi-interactive setting for semantic analysis of film.
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Motivated by existing cinematic conventions known as film grammar, we proposed a computational approach to determine tempo as a high-level movie content descriptor as well as means for deriving dramatic story sections and events occurring in movies. Movie tempo is extracted from two easily computed aspects in our approach: shot length and motion. Story sections and events are generally associated with changes in tempo, and are thus identified by edges located in the tempo function. In this paper, we analyze our initial founding of the tempo function on the basis that the distribution of both shot length and motion in movies is normal. Given that the distribution of shot length is approximately Weibull as confirmed in our experiments, we examine the impact of modelling and modifying the contributions of shot length to tempo. We derive an appropriate normalization function that faithfully encapsulates the role of shot length in tempo perception, and analyze the changes to the story sections identified in films.
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To enable high-level semantic indexing of video, we tackle the problem of automatically structuring motion pictures into meaningful story units, namely scenes. In our recent work, drawing guidance from film grammar, we proposed an algorithmic solution for extracting scenes in motion pictures based on a shot neighborhood color coherence measure. In this paper, we extend our work by presenting various refinement mechanisms, inspired by the knowledge of film devices that are brought to bear while crafting scenes, to further improve the results of the scene detection algorithm. We apply the enhanced algorithm to ten motion pictures and demonstrate the resulting improvements in performance.
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Bostwick, A.L. Censorship of motion picture films. Report to the City Council; p. 5-17.
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Mode of access: Internet.
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General note: Title and date provided by Bettye Lane.
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This paper presents a new study on the application of the framework of Computational Media Aesthetics to the problem of automated understanding of film. Leveraging Film Grammar as the means to closing the "semantic gap" in media analysis, we examine film rhythm, a powerful narrative concept used to endow structure and form to the film compositionally and enhance its lyrical quality experientially. The novelty of this paper lies in the specification and investigation of the rhythmic elements that are present in two cinematic devices; namely motion and editing patterns, and their potential usefulness to automated content annotation and management systems. In our rhythm model, motion behavior is classified as being either nonexistent, fluid or staccato for a given shot. Shot neighborhoods in movies are then grouped by proportional makeup of these motion behavioral classes to yield seven high-level rhythmic arrangements that prove to be adept at indicating likely scene content (e.g. dialogue or chase sequence) in our experiments. The second part of our investigation presents a computational model to detect editing patterns as either metric, accelerated, decelerated or free. Details of the algorithm for the extraction of these classes are presented, along with experimental results on real movie data. We show with an investigation of combined rhythmic patterns that, while detailed content identification via rhythm types alone is not possible by virtue of the fact that film is not codified to this level in terms of rhythmic elements, analysis of the combined motion/editing rhythms can allow us to determine that the content has changed and hypothesize as to why this is so. We present three such categories of change and demonstrate their efficacy for capturing useful film elements (e.g. scene change precipitated by plot event), by providing data support from five motion pictures.
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This paper addresses the challenge of bridging the semantic gap that exists between the simplicity of features that can be currently computed in automated content indexing systems and the richness of semantics in user queries posed for media search and retrieval. It proposes a unique computational approach to extraction of expressive elements of motion pictures for deriving high-level semantics of stories portrayed, thus enabling rich video annotation and interpretation. This approach, motivated and directed by the existing cinematic conventions known as film grammar, as a first step toward demonstrating its effectiveness, uses the attributes of motion and shot length to define and compute a novel measure of tempo of a movie. Tempo flow plots are defined and derived for a number of full-length movies and edge analysis is performed leading to the extraction of dramatic story sections and events signaled by their unique tempo. The results confirm tempo as a useful high-level semantic construct in its own right and a promising component of others such as rhythm, tone or mood of a film. In addition to the development of this computable tempo measure, a study is conducted as to the usefulness of biasing it toward either of its constituents, namely, motion or shot length. Finally, a refinement is made to the shot length normalizing mechanism, driven by the peculiar characteristics of shot length distribution exhibited by movies. Results of these additional studies, and possible applications and limitations are discussed.
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This paper proposes a unique computational approach to extraction of expressive elements of motion pictures for deriving high level semantics of stories portrayed, thus enabling better video annotation and interpretation systems. This approach, motivated and directed by the existing cinematic conventions known as film grammar, as a first step towards demonstrating its effectiveness, uses the attributes of motion and shot length to define and compute a novel measure of tempo of a movie. Tempo flow plots are defined and derived for four full-length movies and edge analysis is performed leading to the extraction of dramatic story sections and events signaled by their unique tempo. The results confirm tempo as a useful attribute in its own right and a promising component of semantic constructs such as tone or mood of a film.
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This paper forms a continuation of our work focused on exploiting film grammar for the task of automated film understanding. We examine film rhythm, a powerful narrative concept used to endow structure and form to the film compositionally and to enhance its lyrical quality experientially. Of the many, often complex, cinematic devices contributing to film rhythm, this paper investigates the rhythmic elements that are present in edited sequences of shots, and presents a novel computational model to detect shot structural rhythm as either metric, accelerated, decelerated, or free. Details of the algorithm for the extraction of these editing rhythm classes are presented, along with experimental results on real movie data. Following this we study the usefulness of combining the rhythmic patterns induced through both motion and editing in film. We show that, whilst detailed content identification via rhythm types alone is not possible by virtue of the fact that film is not codified to this level in terms of rhythmic elements, analysis of the combined motion/shot rhythm can allow us to determine that the content has changed and hypothesize as to why this is so. We present 3 such categories of change and demonstrate their efficacy for capturing useful film elements (e.g., scene change precipitated by plot event), by providing data support from 5 motion pictures.