WICED 2017

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/2631243

Lyon, France | April 2017

Preface and Table of Contents

Reasoning and Knowledge

Declarative Spatial Reasoning for Intelligent Cinematography

[full paper

] [meta data

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Mehul Bhatt, Carl Schultz, Jakob Suchan, and Przemyslaw Walega

La Caméra Enchantée

[full paper

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Jarek Rossignac

Implementing Hitchcock - the Role of Focalization and Viewpoint

[full paper

] [meta data

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Quentin Galvane and Rémi Ronfard

CaMor: Screw Interpolation between Perspective Projections of Partial Views of Rectangular Images

[full paper

] [meta data

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Gokul Raghuraman, Nicholas Barrash, and Jarek Rossignac

Styles and Challenges

Inferring the Structure of Action Movies

[full paper

] [meta data

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Danila Potapov, Matthijs Douze, Jérôme Revaud, Zaid Harchaoui, and Cordelia Schmid

Analyzing Elements of Style in Annotated Film Clips

[full paper

] [meta data

]

Hui-Yin Wu, Quentin Galvane, Christophe Lino, and Marc Christie

Five Challenges for Intelligent Cinematography and Editing

[full paper

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Rémi Ronfard

Live-action Cinematography

Zooming On All Actors: Automatic Focus+Context Split Screen Video Generation

[full paper

] [meta data

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Moneish Kumar, Vineet Gandhi, Rémi Ronfard, and Michael Gleicher

Pano2Vid: Automatic Cinematography for Watching 360° Videos

[full paper

] [meta data

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Yu-Chuan Su, Dinesh Jayaraman, and Kristen Grauman

A Probabilistic Logic Programming Approach to Automatic Video Montage

[full paper

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Bram Aerts, Toon Goedemé, and Joost Vennekens

Automatic Camera Selection and PTZ Canvas Steering for Autonomous Filming of Reality TV

[full paper

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Timothy Callemein, Wiebe Van Ranst, and Toon Goedemé

Human-Machine Collaborations in Film

Making Movies from Make-Believe Games

[full paper

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Adela Barbulescu, Maxime Garcia, Dominique Vaufreydaz, Marie Paule Cani, and Rémi Ronfard

Design of an Intelligent Navigation System for Participative Computer Animation

[full paper

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Iou-Shiuan Liu, Tsai-Yen Li, and Marc Christie

Using ECPs for Interactive Applications in Virtual Cinematography

[full paper

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Hui-Yin Wu, Tsai-Yen Li, and Marc Christie

Film Ties: A Web-based Virtual 3D Lab for Teaching the Film Art from Script to Blocking

[full paper

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William Bares, Caroline Requierme, and Elizabeth Obisesan

BibTeX (WICED 2017)

@inproceedings{10.2312:wiced.20171065,

booktitle = {Eurographics Workshop on Intelligent Cinematography and Editing},

editor = {William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
},
title = {{Implementing Hitchcock - the Role of Focalization and Viewpoint}},

author = {Galvane, Quentin and 
Ronfard, Rémi
},
year = {2017},

publisher = {The Eurographics Association},

ISSN = {2411-9733},
ISBN = {978-3-03868-031-4},

DOI = {10.2312/wiced.20171065}

}

@inproceedings{10.2312:wiced.20171067,

booktitle = {Eurographics Workshop on Intelligent Cinematography and Editing},

editor = {William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
},
title = {{Inferring the Structure of Action Movies}},

author = {Potapov, Danila and 
Douze, Matthijs and 
Revaud, Jérôme and 
Harchaoui, Zaid and 
Schmid, Cordelia
},
year = {2017},

publisher = {The Eurographics Association},

ISSN = {2411-9733},
ISBN = {978-3-03868-031-4},

DOI = {10.2312/wiced.20171067}

}

@inproceedings{10.2312:wiced.20171069,

booktitle = {Eurographics Workshop on Intelligent Cinematography and Editing},

editor = {William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
},
title = {{Five Challenges for Intelligent Cinematography and Editing}},

author = {Ronfard, Rémi
},
year = {2017},

publisher = {The Eurographics Association},

ISSN = {2411-9733},
ISBN = {978-3-03868-031-4},

DOI = {10.2312/wiced.20171069}

}

@inproceedings{10.2312:wiced.20171068,

booktitle = {Eurographics Workshop on Intelligent Cinematography and Editing},

editor = {William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
},
title = {{Analyzing Elements of Style in Annotated Film Clips}},

author = {Wu, Hui-Yin and 
Galvane, Quentin and 
Lino, Christophe and 
Christie, Marc
},
year = {2017},

publisher = {The Eurographics Association},

ISSN = {2411-9733},
ISBN = {978-3-03868-031-4},

DOI = {10.2312/wiced.20171068}

}

@inproceedings{10.2312:wiced.20171070,

booktitle = {Eurographics Workshop on Intelligent Cinematography and Editing},

editor = {William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
},
title = {{Zooming On All Actors: Automatic Focus+Context Split Screen Video Generation}},

author = {Kumar, Moneish and 
Gandhi, Vineet and 
Ronfard, Rémi and 
Gleicher, Michael
},
year = {2017},

publisher = {The Eurographics Association},

ISSN = {2411-9733},
ISBN = {978-3-03868-031-4},

DOI = {10.2312/wiced.20171070}

}

@inproceedings{10.2312:wiced.20171072,

booktitle = {Eurographics Workshop on Intelligent Cinematography and Editing},

editor = {William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
},
title = {{A Probabilistic Logic Programming Approach to Automatic Video Montage}},

author = {Aerts, Bram and 
Goedemé, Toon and 
Vennekens, Joost
},
year = {2017},

publisher = {The Eurographics Association},

ISSN = {2411-9733},
ISBN = {978-3-03868-031-4},

DOI = {10.2312/wiced.20171072}

}

@inproceedings{10.2312:wiced.20171071,

booktitle = {Eurographics Workshop on Intelligent Cinematography and Editing},

editor = {William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
},
title = {{Pano2Vid: Automatic Cinematography for Watching 360° Videos}},

author = {Su, Yu-Chuan and 
Jayaraman, Dinesh and 
Grauman, Kristen
},
year = {2017},

publisher = {The Eurographics Association},

ISSN = {2411-9733},
ISBN = {978-3-03868-031-4},

DOI = {10.2312/wiced.20171071}

}

@inproceedings{10.2312:wiced.20171073,

booktitle = {Eurographics Workshop on Intelligent Cinematography and Editing},

editor = {William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
},
title = {{Automatic Camera Selection and PTZ Canvas Steering for Autonomous Filming of Reality TV}},

author = {Callemein, Timothy and 
Ranst, Wiebe Van and 
Goedemé, Toon
},
year = {2017},

publisher = {The Eurographics Association},

ISSN = {2411-9733},
ISBN = {978-3-03868-031-4},

DOI = {10.2312/wiced.20171073}

}

@inproceedings{10.2312:wiced.20171075,

booktitle = {Eurographics Workshop on Intelligent Cinematography and Editing},

editor = {William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
},
title = {{Design of an Intelligent Navigation System for Participative Computer Animation}},

author = {Liu, Iou-Shiuan and 
Li, Tsai-Yen and 
Christie, Marc
},
year = {2017},

publisher = {The Eurographics Association},

ISSN = {2411-9733},
ISBN = {978-3-03868-031-4},

DOI = {10.2312/wiced.20171075}

}

@inproceedings{10.2312:wiced.20171077,

booktitle = {Eurographics Workshop on Intelligent Cinematography and Editing},

editor = {William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
},
title = {{Film Ties: A Web-based Virtual 3D Lab for Teaching the Film Art from Script to Blocking}},

author = {Bares, William and 
Requierme, Caroline and 
Obisesan, Elizabeth
},
year = {2017},

publisher = {The Eurographics Association},

ISSN = {2411-9733},
ISBN = {978-3-03868-031-4},

DOI = {10.2312/wiced.20171077}

}

Browse

Now showing 1 - 10 of 10

Implementing Hitchcock - the Role of Focalization and Viewpoint
(The Eurographics Association, 2017) Galvane, Quentin; Ronfard, Rémi; William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
Focalization and viewpoint are important aspects of narrative movie-making that need to be taken into account by cinematography and editing. In this paper, we argue that viewpoint can be determined from the first principles of focalization in the screenplay and adherence to a slightly modified version of Hitchcock's rule in cinematography and editing. With minor changes to previous work in automatic cinematography and editing, we show that this strategy makes it possible to easily control the viewpoint in the movie by rewriting and annotating the screenplay. We illustrate our claim with four versions of a moderately complex movie scene obtained by focalizing on its four main characters, with dramatically different camera choices.
Inferring the Structure of Action Movies
(The Eurographics Association, 2017) Potapov, Danila; Douze, Matthijs; Revaud, Jérôme; Harchaoui, Zaid; Schmid, Cordelia; William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
While important advances were recently made towards temporally localizing and recognizing specific human actions or activities in videos, efficient detection and classification of long video chunks belonging to semantically-defined categories remains challenging. Examples of such categories can be found in action movies, whose storylines often follow a standardized structure corresponding to a sequence of typical segments such as ''pursuit'', ''romance'', etc. We introduce a new dataset, Action Movie Franchises, consisting of a collection of Hollywood action movie franchises. We define 11 non-exclusive semantic categories that are broad enough to cover most of the movie footage. The corresponding events are annotated as groups of video shots, possibly overlapping. We propose an approach for localizing events based on classifying shots into categories and learning the temporal constraints between shots. We show that temporal constraints significantly improve the classification performance. We set up an evaluation protocol for event localization as well as for shot classification, depending on whether movies from the same franchise are present or not in the training data.
Five Challenges for Intelligent Cinematography and Editing
(The Eurographics Association, 2017) Ronfard, Rémi; William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
In this position paper, we propose five challenges for advancing the state of the art in intelligent cinematography and editing by taking advantage of the huge quantity of cinematographic data (movies) and metadata (movie scripts) available in digital formats. This suggests a data-driven approach to intelligent cinematography and editing, with at least five scientific bottlenecks that need to be carefully analyzed and resolved.we briefly describe them and suggest some possible avenues for future research in each of those new directions.
Analyzing Elements of Style in Annotated Film Clips
(The Eurographics Association, 2017) Wu, Hui-Yin; Galvane, Quentin; Lino, Christophe; Christie, Marc; William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
This paper presents an open database of annotated film clips together with an analysis of elements of film style related to how the shots are composed, how the transitions are performed between shots and how the shots are sequenced to compose a film unit. The purpose is to initiate a shared repository pertaining to elements of film style which can be used by computer scientists and film analysts alike. Though both research communities rely strongly on the availability of such information to foster their findings, current databases are either limited to low-level features (such as shots lengths, color and luminance information), contain noisy data, or are not available to the communities. The data and analysis we provide open exciting perspectives as to how computational approaches can rely more thoroughly on information and knowledge extracted from existing movies, and also provide a better understanding of how elements of style are arranged to construct a consistent message.
Zooming On All Actors: Automatic Focus+Context Split Screen Video Generation
(The Eurographics Association, 2017) Kumar, Moneish; Gandhi, Vineet; Ronfard, Rémi; Gleicher, Michael; William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
Stage performances can be easily captured using a high resolution camera but these are often difficult to watch because actor faces are too small. We present a novel approach to create a split screen video that incorporates both the context as well as the close-up details of the actors. Our system takes as input the static recording of a stage performance and tracking information about the actor positions, and generates a video with a wide master shot and a set of close-ups of all identified actors and hence showing a focus+context view that shows both the overall action as well as the details of actor faces. The key to our approach is to compute these camera motions such that they are cinematically valid close-ups and to ensure that the set of views of the different actors are properly coordinated and presented. The close-up views are created as virtual camera movements by applying panning, cropping and zooming to the source video. We pose the computation of camera motions as convex optimization that creates detailed views and smooth movements, subject to cinematic constraints such as not cutting faces with the edge of the frame. Additional constraints allow for the interaction amongst the close up views of each actor, causing them to merge seamlessly when actors are close. Generated views are then placed in a layout that preserves the spatial relationships between actors. We demonstrate our results on a variety of video sequences from theatre and dance performances.
A Probabilistic Logic Programming Approach to Automatic Video Montage
(The Eurographics Association, 2017) Aerts, Bram; Goedemé, Toon; Vennekens, Joost; William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
Hiring a professional camera crew to cover an event such as a lecture, sports game or musical performance may be prohibitively expensive. The CAMETRON project aims at drastically reducing this cost by developing an (almost) fully automated system that can produce video recordings of such events with a quality similar to that of a professional crew. This system consists of different components, including intelligent Pan-Tilt-Zoom cameras and UAVs that act as ''virtual camera men''. To combine the footage of these different cameras into a single coherent and pleasant-to-watch video, a ''virtual editor'' is needed. Human editors typically follow a number of different-and sometimes contradictory-cinematographic ''rules'' to accomplish this task. To develop our virtual editor, we will follow a declarative approach, in which we explicitly represent these rules. This approach has the benefit that it offers a great deal of flexibility in deciding which rules should be taken into account and how they should take priority over each other. It also allows us to reuse the same knowledge to perform different tasks: we cannot only use the rules to generate a montage, but also to evaluate the quality of a given montage or to learn certain properties of good montages from given examples. To represent the rules, we need a suitable knowledge representation language. A particular challenge is that cinematographic rules are not strict: they are guidelines that are typically followed, but not always. Indeed, the rules may sometimes contradict each other, and even if they do not, a human editor may still choose to ignore a rule, simply because the result ''feels'' better. A virtual editor should therefore not rigidly follow the rules, but it should sometimes deviate from them in order to give the montage a more interesting and natural flavour, thereby mimicking the creativity of a human editor. For this reason, we have chosen to make use of the Probabilistic Logic Programming language CP-logic and its implementation in the Problog system, which allows us to represent these rules in a non-deterministic way. This has the additional benefit that-just like a human editor-the system is able to produce different montages from the same input streams. The proposed editing system takes as input a number of different video streams, together with a computer vision analysis of each of these streams. For each frame in each stream, we expect this analysis to provide information, such as the presence of people, the type of shot and the action the main subject performs. The goal of our editing system is to decide for each point in time which of the available camera feeds will be used. Those decisions are made based on the cinematographic model described in the paper. The output of the system is the single video stream that is thus constructed. We demonstrate that the resulting system is able to produce real-time edits of different video streams. In order to verify the quality of the resulting montage, we subjected the virtual editor to a ''Turing test'': we asked 58 test subjects to distinguish between the output of our system and a professionally made montage of the same video streams. 31 subjects correctly identified the professionally edited clip. The difference between this outcome and one that could be produced by random guessing is not statistically significant. We conclude that our editing system indeed provides a good approximation of the quality delivered by a professional editor for this particular case study of lecture recording.
Pano2Vid: Automatic Cinematography for Watching 360° Videos
(The Eurographics Association, 2017) Su, Yu-Chuan; Jayaraman, Dinesh; Grauman, Kristen; William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
We introduce the novel task of Pano2Vid --- automatic cinematography in panoramic 360° videos. Given a 360° video, the goal is to direct an imaginary camera to virtually capture natural-looking normal field-of-view (NFOV) video. By selecting "where to look" within the panorama at each time step, Pano2Vid aims to free both the videographer and the end viewer from the task of determining what to watch. Towards this goal, we first compile a dataset of 360° videos downloaded from the web, together with human-edited NFOV camera trajectories to facilitate evaluation. Next, we propose AutoCam, a data-driven approach to solve the Pano2Vid task. AutoCam leverages NFOV web video to discriminatively identify space-time "glimpses" of interest at each time instant, and then uses dynamic programming to select optimal human-like camera trajectories. Through experimental evaluation on multiple newly defined Pano2Vid performance measures against several baselines, we show that our method successfully produces informative videos that could conceivably have been captured by human videographers.
Automatic Camera Selection and PTZ Canvas Steering for Autonomous Filming of Reality TV
(The Eurographics Association, 2017) Callemein, Timothy; Ranst, Wiebe Van; Goedemé, Toon; William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
Reality TV shows that follow people in their day-to-day lives are not a new concept. However, the traditional methods used in the industry require a lot of manual labor and need the presence of at least one physical camera man. Because of this, the subjects tend to behave differently when they are aware of being recorded. This paper presents an approach to follow people in their day-to-day lives, for long periods of time (months to years), while being as unobtrusive as possible. To do this, we use unmanned cinematographically-aware cameras hidden in people's houses. Our contribution in this paper is twofold: First, we create a system to limit the amount of recorded data by intelligently controlling a video switch matrix, in combination with a multi-channel recorder. Second, we create a virtual camera man by controlling a PTZ camera to automatically make cinematographically pleasing shots. Throughout this paper, we worked closely with a real camera crew, enabling us to compare the results of our system to the work of trained professionals. This work was originally published in MVA 2017, as T. Callemein, W. Van Ranst and T. Goedemé, "The Autonomous hidden Camera Crew".
Design of an Intelligent Navigation System for Participative Computer Animation
(The Eurographics Association, 2017) Liu, Iou-Shiuan; Li, Tsai-Yen; Christie, Marc; William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
In this paper, we will propose a novel way of interactive entertainment, called Participative Computer Animation, allowing a user to participate in a computer animated story as an observer. We consider this form of entertainment as a kind of interactive storytelling, in which the presentation and perception of the story is under the control of a user through a first-person camera. As the animation of the story unfolds, the user needs to follow and view the relevant events, a complex task which requires him to navigate in the 3D environment, and hence reduce his immersion. We therefore propose to design an intelligent navigation mechanism, in which the system can voluntarily assist the user in reaching some designated best view configurations under time constraint. We have implemented such a system and invited a few users in a pilot study to evaluate the system and provide feedback. The experimental results show that our participative computer animation system can enhance the sense of presence while the intelligent navigation mechanism can improve the quality of perceiving the animated story.
Film Ties: A Web-based Virtual 3D Lab for Teaching the Film Art from Script to Blocking
(The Eurographics Association, 2017) Bares, William; Requierme, Caroline; Obisesan, Elizabeth; William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard
Film production education programs include hands-on training in script writing, planning blocking of performers and cameras on set, camera operation, editing to select the best footage at each beat of the story, and expert critiques to help students improve their work. Unfortunately, this ideal form of active, hands-on learning for film production requires access to specialized equipment, movie sets, and expert film instructors. Complementary film studies education programs teach how to read the visual language of a film to breakdown each shot to understand how and why it works. Both film production and theory education involve a social component in which students collectively screen, critique, and breakdown shots seen in the films. This short paper presents work in progress to develop a Web-based virtual 3D lab, which can be used to simulate the central learning activities found in film production and film studies educational programs. The system can also be used to crowd source annotated corpora of film, which would serve as a resource for film scholars and machine-learning algorithms.

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