Film Analysis as Annotation: Exploring Current Tools

Estrada, Liliana Melgar; Hielscher, Eva; Koolen, Marijn; Olesen, Christian Gosvig; Noordegraaf, Julia; Blom, Jaap

doi:10.5749/movingimage.17.2.0040

Cited by 4 publications

(3 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Relational-analytic methods build on previous work in quantitative film studies (Salt, 1974; Tsivian, 2009; Butler, 2014; Baxter, 2014), complementing classical statistical approaches with recent data science techniques. This also echoes existing work in the broader field of digital humanities, traditionally more focused on text and canonical artefacts than on popular audiovisual culture, but that is increasingly contributing scholarship about films and television analysed through computer vision technologies (Estrada et al, 2017; Heftberger, 2018; Mittell, 2019, 2021; Olesen, 2017; Smits and Wevers, 2022; Wevers and Smits, 2020).…”

Section: Machine Vision Cultural Analytics and Videographic Criticismsupporting

confidence: 71%

Creanalytics: Automating the supercut as a form of critical technical practice

Heras

2023

Convergence: The International Journal of Research into New Med

View full text Add to dashboard Cite

Based on the notion of critical technical practice and its resonances with recent debates in digital film and media scholarship, in this article I outline a type of computational practice that aims to couple the relational-analytic powers of machine learning with the explanatory-creative powers of visual narrative. I provisionally call this approach creanalytics. To enact this coupling, I designed a system to annotate and classify a large corpus of film clips, automatically extract fragments from this corpus, and edit them into new compositions, rendered into a computational supercut, which I go on to argue can be understood as the minimal expression of a broader emergent form of media: the computational video essay. Below I describe the most salient technical aspects of this system, analyse the principles of its design, and discuss the methodological and conceptual possibilities of its use as a format that mediates between critics and their networked environments, and between individual media artefacts, their parts, and the larger collections to which they belong.

show abstract

Section: Machine Vision Cultural Analytics and Videographic Criticismsupporting

confidence: 71%

Creanalytics: Automating the supercut as a form of critical technical practice

Heras

2023

Convergence: The International Journal of Research into New Med

View full text Add to dashboard Cite

show abstract

“…Qualitative data analysis is a fundamental framework for digital humanities (DH) scholars, and the landscape of software packages for this task is commensurately large. We refer the reader to Melgar et al [MEHK∗17] for a broad survey that includes an extensive comparison of over 50 existing tools related to film analysis and their purpose within DH, grouped by functionality type. Three of those important functionalities are partially covered in VIAN: professional video annotation, qualitative analysis, and automatic video analysis.…”

Section: Related Workmentioning

confidence: 99%

“…While traditional tools were mainly desktop applications, browser‐based solutions have recently become more popular [CLA, Lig, SAT]. While all these annotation tools were developed for film analysis, they do not feature color visualizations (see [Giu10,Giu14,MEHK∗17,Flu17] for an overview).…”

Section: Introductionmentioning

confidence: 99%

VIAN: A Visual Annotation Tool for Film Analysis

Halter

Ballester-Ripoll

Flückiger

et al. 2019

Computer Graphics Forum

View full text Add to dashboard Cite

While color plays a fundamental role in film design and production, existing solutions for film analysis in the digital humanities address perceptual and spatial color information only tangentially. We introduce VIAN, a visual film annotation system centered on the semantic aspects of film color analysis. The tool enables expert‐assessed labeling, curation, visualization and Classification of color features based on their perceived context and aesthetic quality. It is the first of its kind that incorporates foreground‐background information made possible by modern deep learning segmentation methods. The proposed tool seamlessly integrates a multimedia data management system, so that films can undergo a full color‐oriented analysis pipeline.

show abstract

Modeling narrative features in TV series: coding and clustering analysis

Rocchi

Pescatore

2022

Humanit Soc Sci Commun

View full text Add to dashboard Cite

TV series have gained both economic and cultural relevance. Their development over time can hardly be traced back to the simple programmatic action of creative intentionality. Instead, TV series might be studied as narrative ecosystems with emergent trends and patterns. This paper aims to boost quantitative research in the field of media studies, first considering a comparative and data-driven study of the narrative features in the US medical TV series, one of the most popular and longest-running genres on global television. Based on a corpus of more than 400 h of video, we investigate the storytelling evolution of eight audiovisual serial products by identifying three main narrative features (i.e., isotopies). The implemented schematization allows to grasp the basic components of the social interactions showing the strength of the medical genre and its ability to rebuild, in its microcosm, the essential traits of the human macrocosm where random everyday life elements (seen in the medical cases plot) mix and overlap with working and social relationships (professional plot) and personal relationships (sentimental plot). This study relies on data-driven research that combines content analysis and clustering analysis. It significantly differs from traditional studies regarding the narrative features of medical dramas and broadly the field of television studies. We proved that the three isotopies are good descriptors for the medical drama genre and identified four narrative profiles which emphasize the strong stability of these serial products. Contrary to what is often taken for granted in many interpretative studies, creative decisions rarely significantly change the general narrative aspects of the wider series.

show abstract

Film Analysis as Annotation: Exploring Current Tools

Cited by 4 publications

References 18 publications

Creanalytics: Automating the supercut as a form of critical technical practice

Creanalytics: Automating the supercut as a form of critical technical practice

VIAN: A Visual Annotation Tool for Film Analysis

Modeling narrative features in TV series: coding and clustering analysis

Contact Info

Product

Resources

About