Speculative Design for a Nodal Screenplay

1994

Abstract Describes a system, IDIC, which can generate a video sequence according to a story plan by selecting appropriate segments from an archive of annotated video. IDIC uses a simple planner to generate its stories. By critically examining the strengths and weaknesses of the representation and algorithm employed in the planner, the authors are able to describe some interesting similarities and differences between planning and video story generation.

Lecture Notes in Computer Science, 2011

Generating interactive narratives as movies requires knowledge in cinematography (camera placement, framing, lighting) and film editing (cutting between cameras). We present a framework for generating a well-edited movie from interactively generated scene contents and cameras. Our system computes a sequence of shots by simultaneously choosing which camera to use, when to cut in and out of the shot, and which camera to cut to.

The School of Creative Arts & Technologies at Ulster University (Magee) has brought together the subject of computing with creative technologies, cinematic arts (film), drama, dance, music and design in terms of research and education. We propose here the development of a flagship computer software platform, SceneMaker, acting as a digital laboratory workbench for integrating and experimenting with the computerprocessing of new theories and methods in these multidisciplinary fields. We discuss the architecture of SceneMaker and relevant technologies for processing within its component modules. SceneMaker will enable the automated production of multimodal animated scenes from film and drama scripts or screenplays. SceneMaker will highlight affective or emotional content in digital storytelling with particular focus on character body posture, facial expressions, speech, non-speech audio, scene composition, timing, lighting, music and cinematography. Applications of SceneMaker include automated simulation of productions.

Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021

Writing a coherent and engaging story is not easy. Creative writers use their knowledge and worldview to put disjointed elements together to form a coherent storyline, and work and rework iteratively toward perfection. Automated visual storytelling (VIST) models, however, make poor use of external knowledge and iterative generation when attempting to create stories. This paper introduces PR-VIST, a framework that represents the input image sequence as a story graph in which it finds the best path to form a storyline. PR-VIST then takes this path and learns to generate the final story via a re-evaluating training process. This framework produces stories that are superior in terms of diversity, coherence, and humanness, per both automatic and human evaluations. An ablation study shows that both plotting and reworking contribute to the model's superiority.

2009

In this paper a modular authoring system for interactive videos is introduced. The system enables the author to edit the video and add annotations like images, text, hyperlinks to defined scenes or the whole video. It provides a video cutting tool to define scenes, a scene graph to realize non-linear flow of the video and a HTML editor to create text and link annotations. A project can be exported to a XML formatted file with a specific schema and Flash video format (flv) files, which can be interpreted by the project's player. The system is designed to be used intuitively.

Contemporary Visual Culture and AI, 2025

The integration of Artificial Intelligence (AI) in video production represents a fundamental transformation in creative workflows, production methodologies, and content distribution. Through a comprehensive review centered on Our T2 Remake (OT2R)-a groundbreaking 2024 collaborative reinterpretation of Terminator 2: Judgment Day by 50 artists using generative AI-this article examines how emerging technologies are reshaping traditional production paradigms. The study employs a systematic methodology combining technical analysis, user behavior patterns, and industry practices to investigate AI's impact on creative workflows and collaborative frameworks. Our findings reveal critical insights into successful AI implementation strategies, highlighting the importance of balancing technological capabilities with human creativity. In particular, OT2R's decentralized production model demonstrates new possibilities for democratic, inclusive filmmaking practices. The analysis extends beyond technical considerations to examine legal, ethical, and cultural implications of AI integration in creative industries. This article contributes to the field by providing both theoretical frameworks and practical insights for AI implementation in video production. The evidence suggests that while AI offers unprecedented creative possibilities, successful integration requires careful consideration of user behavior patterns, workflow dynamics, and ethical constraints. These findings carry significant implications for future production methodologies, indicating how thoughtful AI integration can enhance rather than replace human creativity.

Lecture Notes in Computer Science, 2014

In this work we design a tool for creators of interactive stories to explore the effect of applying camera patterns to achieve high level communicative goals in a 3D animated scenario. We design a pattern language to specify high level communicative goals that are translated into simple or complex camera techniques and transitions, and then flexibly applied over a sequence of character actions. These patterns are linked to a real-movie shot specification database through elements of context such as characters, objects, actions, and emotions. The use of real movies provides rich context information of the film, and allows the users of our tool to replicate the feel and emotion of existing film segments. The story context, pattern language and database are linked through a decision process that we call the virtual director, who reasons on a given story context and communicative goals, translates them into the camera patterns and techniques, and selects suitable shots from the database. Our real-time 3D environment gives the user the freedom to observe and explore the effect of applying communicative goals without worrying about the details of actor positions, scene, or camera placement.

2012

Abstract Creating film content for broadcast is a high pressure and complex activity involving multiple experts and highly specialized equipment. Production teams are under continuous pressure to produce ever more creative and groundbreaking content while reducing the budgets and human resources required.

Knowledge-Based and Intelligent Information and Engineering Systems, 2010

Producing plays, films or animations is a complex and expensive process involving various professionals and media. Our proposed software system, SceneMaker, aims to facilitate this creative process by automatically interpreting natural language film scripts and generating multimodal, animated scenes from them. During the generation of the story content, SceneMaker gives particular attention to emotional aspects and their reflection in fluency and manner of actions, body posture, facial expressions, speech, scene composition, timing, lighting, music and camera work. Related literature and software on Natural Language Processing, in particular textual affect sensing, affective embodied agents, visualisation of 3D scenes and digital cinematography are reviewed. In relation to other work, SceneMaker follows a genre-specific text-to-animation methodology which combines all relevant expressive modalities and is made accessible via web-based and mobile platforms. In conclusion, SceneMaker will enhance the communication of creative ideas providing quick pre-visualisations of scenes.

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