Graph-based Shot Type Classification in Large Historical Film Archives

To analyze films and documentaries (indexing, content understanding), a shot type classification is needed.

State-of-the-art approaches use traditional CNN-based methods, which need large datasets for training (CineScale with 792000 frames or MovieShots with 46K shots). To overcome this problem, a Graph-based Shot TypeClassifier (GSTC) is proposed, which is able to classify shots into the following types: Extreme-Long-Shot (ELS), Long-Shot (LS), Medium-Shot (MS), Close-Up (CU), Intertitle (I), and Not Available/Not Clear (NA). The methodology is evaluated on standard datasets as well as a new published dataset: HistShotDS-Ext, including 25000 frames. The proposed Graph-based Shot Type Classifier reaches a classification accuracy of 86%.

Daniel Helm, Florian Kleber, Martin Kampel, Graph-based Shot Type Classification in Large Historical Film Archives, in: Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, vol. 4 (February 2022), 991-998.