Title
Conversation Detection In Feature Films Using Finite State Machines
Abstract
In this paper, we address the problem of detecting the conversation scenes from feature films and propose and efficient and robust method for the stated problem. This method utilizes the structural information of the movie scenes with the combination of the low-level and mid-level features. We propose and demonstrate that a Finite State Machine (FSM) is suitable for detecting movie scenes with conversational settings. Tow major characteristics of motion pictures, motion and audio, are used in our approach. The transitions of the FSM are determined by two mid-level features of each shot in the scene: the activity intensity and the face identity. Our FSM has been experimented on over 50 clips with both positive and negative examples and produces convincing results.
Publication Date
12-20-2004
Publication Title
Proceedings - International Conference on Pattern Recognition
Volume
4
Number of Pages
458-461
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/ICPR.2004.1333801
Copyright Status
Unknown
Socpus ID
10044285149 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/10044285149
STARS Citation
Zhai, Yun; Rasheed, Zeeshan; and Shah, Mubarak, "Conversation Detection In Feature Films Using Finite State Machines" (2004). Scopus Export 2000s. 4754.
https://stars.library.ucf.edu/scopus2000/4754