Who is the Film's Director? Authorship Recognition Based on Shot Features

We show how to perform automatic attribution of movie's authorship by the statistical analysis of two simple formal features: the length of camera takes (shot duration), and the distance between the camera and the subject (shot scale). Experiments include 143 films by eight distinguishable directors over 70 years of historiography of author cinema.

[1]  Alberto Signoroni,et al.  Shot Scale Analysis in Movies by Convolutional Neural Networks , 2018, 2018 25th IEEE International Conference on Image Processing (ICIP).

[2]  Eric O. Postma,et al.  Toward Discovery of the Artist's Style: Learning to recognize artists by their artworks , 2015, IEEE Signal Processing Magazine.

[3]  Jean Luc Godard.  2 ou 3 choses que je sais d'elle. , 2002 .

[4]  Riccardo Leonardi,et al.  Affective analysis on patterns of shot types in movies , 2011, 2011 7th International Symposium on Image and Signal Processing and Analysis (ISPA).

[5]  Tao Mei,et al.  Contextual Video Recommendation by Multimodal Relevance and User Feedback , 2011, TOIS.

[6]  Jean-Luc Godard.  Alphaville, une étrange aventure de Lemmy Caution : film , 1965 .

[7]  Jean Luc Godard,et al.  Bande à part , 2013 .

[8]  Loong Fah Cheong,et al.  Affective understanding in film , 2006, IEEE Trans. Circuits Syst. Video Technol..

[9]  Yaser Sheikh,et al.  On the use of computable features for film classification , 2005, IEEE Transactions on Circuits and Systems for Video Technology.

[10]  Dumitru Erhan,et al.  Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[11]  Tibor Pólya,et al.  Watching closely: Spatial distance influences theory of mind responding in film viewers , 2016 .

[12]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[13]  Riccardo Leonardi,et al.  A Connotative Space for Supporting Movie Affective Recommendation , 2011, IEEE Transactions on Multimedia.

[14]  T. Smith.  The attentional theory of cinematic continuity , 2012 .

[15]  Riccardo Leonardi,et al.  Emotional identity of movies , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[16]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[17]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[18]  Kaitlin L. Brunick,et al.  Quicker, faster, darker: Changes in Hollywood film over 75 years , 2011, i-Perception.

[19]  Vasileios Mezaris,et al.  Fast shot segmentation combining global and local visual descriptors , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[20]  B. Salt.  Moving into Pictures: More on Film History, Style, and Analysis , 2006 .