RT Journal Article
T1 QuickLook: 												Movie summarization using scene-based leading characters with psychological cues fusion
A1 Haq, Ijaz Ul
A1 Muhammad, Khan
A1 Hussain, Tanveer
A1 Ser, Javier Del
A1 Sajjad, Muhammad
A1 Baik, Sung Wook
AB Due to recent advances in the film industry, the production of movies has grown exponentially, which has led to challenges in what is referred to as discoverability: given the overwhelming number of choices, choosing which film to watch has become a tedious task for audiences. Movie summarization (MS) could help, as it presents the central theme of the movie in a compact format and makes browsing more efficient for the audience. In this paper, we present an automatic MS framework coined as ‘QuickLook’, which identifies the leading characters and fuses multiple cues extracted from a movie. Firstly, the movie data is preprocessed for its division into scenes, followed by shot segmentation. Secondly, the leading characters in each segmented scene are determined. Next, four visual cues that capture the film's scenic beauty, memorability, informativeness and emotional resonance are extracted from shots containing the leading characters. These extracted features are then intelligently fused based on the assignment of different weights; shots with a fusion score above a certain threshold are selected for the final summary. The proposed MS framework is assessed by comparison with official trailers from ten Hollywood movies, providing a novel baseline for future fair comparison in the MS literature. The proposed framework is shown to outperform other state-of-the-art MS methods in terms of enjoyability and informativeness.
SN 1566-2535
YR 2021
FD 2021-12
LK https://hdl.handle.net/11556/5159
UL https://hdl.handle.net/11556/5159
LA eng
NO Haq , I U , Muhammad , K , Hussain , T , Ser , J D , Sajjad , M & Baik , S W 2021 , ' QuickLook : Movie summarization using scene-based leading characters with psychological cues fusion ' , Information Fusion , vol. 76 , pp. 24-35 . https://doi.org/10.1016/j.inffus.2021.04.016
NO Publisher Copyright: © 2021 Elsevier B.V.
NO This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1A2B5B01070067 ). Javier Del Ser also acknowledges funding support from the Basque Government through its EMAITEK and ELKARTEK funding programs, as well as the consolidated research group grant MATHMODE ( IT1294–19 ) provided by this institution.
DS TECNALIA Publications
RD 28 sept 2024