Muszynski, M., Kostoulas, T., Lombardo, P., Pun, T. and Chanel, T., 2018. Aesthetic Highlight Detection in Movies Based on Synchronization of Spectators’ Reactions. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 14 (3), 68.
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DOI: 10.1145/3175497
Abstract
Detection of aesthetic highlights is a challenge for understanding the affective processes taking place during movie watching. In this paper we study spectators’ responses to movie aesthetic stimuli in a social context. Moreover, we look for uncovering the emotional component of aesthetic highlights in movies. Our assumption is that synchronized spectators’ physiological and behavioral reactions occur during these highlights because: (i) aesthetic choices of filmmakers are made to elicit specific emotional reactions (e.g. special effects, empathy and compassion toward a character, etc.) and (ii) watching a movie together causes spectators’ affective reactions to be synchronized through emotional contagion. We compare different approaches to estimation of synchronization among multiple spectators’ signals, such as pairwise, group and overall synchronization measures to detect aesthetic highlights in movies. The results show that the unsupervised architecture relying on synchronization measures is able to capture different properties of spectators’ synchronization and detect aesthetic highlights based on both spectators’ electrodermal and acceleration signals. We discover that pairwise synchronization measures perform the most accurately independently of the category of the highlights and movie genres. Moreover, we observe that electrodermal signals have more discriminative power than acceleration signals for highlight detection.
Item Type: | Article |
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Additional Information: | Article to be published in ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) |
Uncontrolled Keywords: | synchronization, dynamical systems, physiological signals, behavioral signals; aesthetic experience; aesthetic highlight detection; video summarization; affective computing |
Group: | Faculty of Science & Technology |
ID Code: | 30177 |
Deposited By: | Symplectic RT2 |
Deposited On: | 11 Feb 2018 23:14 |
Last Modified: | 14 Mar 2022 14:08 |
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