The empirical analysis of film style
The analysis of film style by empirical means – i.e. the use of statistics – is an important part of film studies. It is also an important part of other disciplines – information management, research on emotion, advertising, computational media aesthetics – and this tends to be overlooked by film scholars. This week’s post includes a range of references to the analysis of film style – and most of these can be accessed for free on the internet.
References to books may only be available through Google Books, in which case the previews available may be limited. As a general rule, I have not included film studies texts that refer to statistics of film style unless they deal in some way with methods of analysis. If a piece is available online but only through a subscription service I have not included a link. The links were correct as of the date of posting, but if anyone finds a broken link let me know.
This list is by no means exhaustive, but it does give a range of papers that bring new approaches to film studies in areas that have not really been explored and which can enable film scholars to link together different fields: just how does the fast cutting of adverts have an emotional impact on consumers? How do we define genres in terms of their quantitative features rather than the qualitative?
Adams B 2003 Where does computational media aesthetics fit? IEEE Multmiedia 10 (3): 18-27.
Adams B, Dorai C, and Venkatesh S 2002 Formulating film tempo: the computational media aesthetics methodology in practice, in C Dorai and S Venkatesh (eds) Media Computing: Computational Media Aesthetics. Norwell, MA: Kluwer Academic Publishers: 57-79.
Adams B, Dorai C, and Venkatesh S 2000 Role of shot length in characterizing tempo and dramatic story sections in motion pictures, IEEE Pacific Rim Conference on Multimedia, 13-15 December 2000, Sydney, Australia: 54–57.
Adams B, Dorai C, and Venkatesh S 2000 Study of shot length and motion as contributing factors to movie tempo, 8th ACM International Conference on Multimedia, 30 October – 3 November 2000, Los Angeles, CA: 353–355.
Adams B, Dorai C, and Venkatesh S 2002 Finding the beat: an analysis of the rhythmic elements of motion pictures, The 5th Asian Conference on Computer Vision, 23-25 January 2002, Melbourne, Australia.
Bordwell D and Thompson K 1985 Toward a scientific film history? Quarterly Review of Film Studies 10 (3): 224–237.
Brandt M 1994 Traditional film editing vs. electronic nonlinear film editing: a comparison of feature films, Nonlinear. NB: There’s no description of the statistical tests used in this study even though it states that the results are statistically significant. As no value for α is given, it is hard to judge what ‘statistically significant’ means in this context.
Buckland W 2008 What does the statistical style analysis of film involve? Literary and Linguistic Computing 23 (2): 219-230. NB: This is a review of Barry Salt’s Moving into Pictures (see below), and contains an error (confusing the correlation coefficient for the coefficient of determination) that is not in Salt’s book.
Dorai C and Venkatesh S 2001 Computational media aesthetics: finding meaning beautiful, IEEE Multimedia 8 (4): 10-12.
Dorai C and Venkatesh S 2002 Bridging the semantic gap in content management systems – computational media aesthetics, in C Dorai and S Venkatesh (eds) Media Computing: Computational Media Aesthetics. Norwell, MA: Kluwer Academic Publishers: 1-9.
Elsaesser T and Buckland W 2002 Studying Contemporary American Film: A Guide to Movie Analysis. London: Arnold. NB: The chapter on the statistical analysis of film style is available at the cinemetrics website here.
Fishcer S, Leinhart R, and Effelsberg W 1995 Automatic recognition of film genres, Proceedings of the 3rd ACM Multimedia Conference, 9-5 November 1995, San Francisco, CA: 295-304.
Fujita K 1989 Shot length distrbutions in educational TV programmes, Bulletin of the National Institute of Multimedia Education 2: 107-116. This paper can be accessed here by clicking on ‘CiNii Fulltext PDF.’
Fujita K 1992 Shot length distrbutions in educational TV programmes and their characteristics, in H Motoaki, J Misumi, and B Wilpert (eds) Social, Educational, and Clinical Psychology. Proceedings of the 22nd International Congress of Applied Psychology, 22-27 July 1990, Kyoto, Japan: 192. NB: This appears to be a summary of the above paper.
Hanjalic A 2004 Content-based Analysis of Digital Video. Norweel, MA: Kluwer Academic Publishers.
Huang H-Y, Shih W-S, and Hsu W-H 2007 A movie classifier based on visual features, in WG Kropatsch, M Kampel, and A Hanbury (eds) Computer Analysis of Images and Patterns. Proceedings of the 12th International Conference on Computer Analysis of Images and Patterns, 27-29 August 2007, Vienna, Austria: 937-944.
Huang H-Y, Shih W-S, and Hsu W-H 2008 A film classifier based on low-level visual features, Journal of Multimedia 3 (3): 26-33. [The link to this paper has been removed as a bad link].
Kang H-B 2003 Affective content detection using HMMs, Proceedings of the eleventh ACM International Conference on Multimedia 2-8 November 2003, Berkeley, CA: 259-262.
Kang H-B 2003 Emotional event detection using relevance feedback, Proceedings of the International Conference on Image Processing, 14-18 September 2003, Barcelona, Spain: 721-724.
Kang H-B 2003 Affective contents retrieval from video with relevance feedback, in TMT Sembok, HB Zaman, H Chen, S Urs, and SH Myaeng (eds) Digital Libraries: Technology and Management of Indigenous Knowledge for Global Access. Proceedings of the 6th International Conference on Asian Digital Libraries, 8-12 December 2003, Kuala Lumpur, Malaysia: 243-252.
Maclachlan J and Logan M 1993 Camera shot length in commercials and their memorability and presuasiveness, Journal of Advertising Research 33 (2): 57-61.
Mittal A, Fah CL, Kassim A, and Pagalthivarthi KV Context-based interpretation and indexing of video data, in U Srinivasan and S Nepal (eds) Managing Multimedia Semantics. Hershey, PA: IRM Press: 77-98.
Nack F 2002 The future of media computing, in C Dorai and S Venkatesh (eds) Media Computing: Computational Media Aesthetics. Norwell, MA: Kluwer Academic Publishers: 159-186.
Nothelfer CE, DeLong JE, and Cutting, JE 2009 Shot structure in Hollywood film, Indiana Undergraduate Journal of Cognitive Science 4: 103-113.
Romatowska A 2004 Pickpocket: A statistical analysis, Offscreen 8 (4).
Rosenbaum J 2000 Is Ozu slow? Senses of Cinema 4.
Salt B 1974 Statistical style analysis of motion pictures, Film Quarterly 28 (1): 13-22.
Salt B 1992 Film Style and Technology: History and Analysis, second edition. London: Starwood.
Salt B 2001 Practical film theory and its application to TV series dramas, Journal of Media Practice 2 (2): 98-113.
Salt B 2006 Moving into Pictures: More on Film History, Style, and Analysis. Starwood, London.
Schaefer R 1997 Editing strategies in television news documentaries, Journal of Communication 47(4): 69-88.
Taskiran CM and Delp EJ 2002 A study on the distribution of shot lengths for video analysis, SPIE Conference on Storage and Retrieval for Media Databases, 20-25 January 2002, San Jose, CA.
Tian Q and Zhang H-J 1999 Video shot detection and analysis: content-based approaches, in CW Chen, Y-Q Zhang (eds) Visual Information Representation, Communication, and Image Processing. New York: Marcel Dekker, Inc: 227-254.
Tiemans R 2004 A content analysis of political speeches on television, in KI Smith, K Kenny, S Moriarty, and G Barbatsis (eds) Handbook of Visual Communication: Theory, Methods, and Media. New York: Routledge: 385-404.
Totaro D 2004 Reflections on the Pickpocket statistical analysis, Offscreen 8 (4).
Truong BT and Venkatesh S 2005 Finding the optimal temporal partitioning of video sequences, Proceedings of IEEE International Conference on Multimedia and Expo, 6-9 July 2005, Amsterdam, Netherlands: 1182-1185.
Tsivian Y 2008 What is cinema? An agnostic answer, Critical Inquiry 34 (4): 754-776.
Vasconcelos N and Lippman A 2000 Statistical models of video structure for content analysis and characterization, IEEE Transactions on Image Processing 9 (1): 3–19.
Young C 2007 Fast editing speed and commercial performance, Admap 483: 30-33.
Young C 2007 Fast-working advertising, Admap 484: 32-34.