Novel approach to determining tempo and dramatic story sections in motion pictures

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

Role of shot length in characterizing tempo and dramatic story sections in motion pictures

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.<br /

Automated film rhythm extraction for scene analysis

This paper examines film rhythm, an important expressive element in motion pictures, based on our ongoing study to exploit film grammar as a broad computational framework for the task of automated film and video understanding. Of the many, more or less elusive, narrative devices contributing to film rhythm, this paper discusses motion characteristics that form the basis of our analysis, and presents novel computational models for extracting rhythmic patterns induced through a perception of motion. In our rhythm model, motion behaviour is classified as being either nonexistent, fluid or staccato for a given shot. Shot neighbourhoods in movies are then grouped by proportional makeup of these motion behavioural 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. Underlying causes for this level of codification in our approach are postulated from film grammar, and are accompanied by detailed demonstration from real movies for the purposes of clarification.<br /

Automated film rhythm extraction for scene analysis

This paper examines film rhythm, an important expressive element in motion pictures, based on our ongoing study to exploit film grammar as a broad computational framework for the task of automated film and video understanding. Of the many, more or less elusive, narrative devices contributing to film rhythm, this paper discusses motion characteristics that form the basis of our analysis, and presents novel computational models for extracting rhythmic patterns induced through a perception of motion. In our rhythm model, motion behaviour is classified as being either nonexistent, fluid or staccato for a given shot. Shot neighbourhoods in movies are then grouped by proportional makeup of these motion behavioural 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. Underlying causes for this level of codification in our approach are postulated from film grammar, and are accompanied by detailed demonstration from real movies for the purposes of clarification.<br /

Toward automatic extraction of expressive elements from motion pictures : tempo

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

Analysis of shot boundary detection techniques on a large video test suite

This thesis investigates how content-based indexing and retrieval systems can be used to analyse digital video. We focus particularly on the challenge of applying colour-analysis methods to large amounts of heterogeneous television broadcast video. Content-based systems are those which attempt to automatically analyse image or video documents by identifying and indexing certain features present in the documents. These features may include colour and texture, shape, and spatial locations. Digital video has become hugely important through the widespread use of the Internet and the increasing number of digital content providers supplying the commercial and domestic markets. The challenge facing the indexing of digital video information in order to support browsing and retrieval by users, is to design systems that can accurately and automatically process large amounts of heterogeneous video. The basic segmentation of video material into shots and scenes is the basic operation in the analysis of video content. Although many published methods of detecting shot boundaries exist, it is d ifficult to compare and contrast the available techniques. This is due to several reasons. Firstly, full system implementation details are not always published and this can make recreation of the systems difficult. Secondly, most systems are evaluated on small, homogeneous sequences of video. These results give little indication how such systems would perform on a broader range of video content types, or indeed how differing content types can affect system performance. As part of an ongoing video indexing and browsing project, our research has focused on the application of different methods of video segmentation to a large and diverse digital video collection. A particular focus is to examine how different segmentation methods perform on different video content types. With this information, it is hoped to develop a system capable of accurately segmenting a wide range of broadcast video. Oilier areas addressed in this thesis include an investigation of evaluation methods for digital video indexing systems, and the use of adaptive thresholds for segmentation of video into shots and scenes