دورية أكاديمية

A lightweight weak semantic framework for cinematographic shot classification

التفاصيل البيبلوغرافية
العنوان: A lightweight weak semantic framework for cinematographic shot classification
المؤلفون: Yuzhi Li, Tianfeng Lu, Feng Tian
المصدر: Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
بيانات النشر: Nature Portfolio, 2023.
سنة النشر: 2023
المجموعة: LCC:Medicine
LCC:Science
مصطلحات موضوعية: Medicine, Science
الوصف: Abstract Shot is one of the fundamental unit in the content structure of a film, which can provide insights into the film-director’s ideas. By analyzing the properties and types of shots, we can gain a better understanding of a film’s visual language. In this paper, we delve deeply into the task of shot type classification, proposing that utilizing multimodal video inputs can effectively improve the accuracy of the task, and that shot type classification is closely related to low-level spatiotemporal semantic features. To this end, we propose a Lightweight Weak Semantic Relevance Framework (LWSRNet) for classifying cinematographic shot types. Our framework comprises two modules: a Linear Modalities Fusion module (LMF Module) capable of fusing an arbitrary number of video modalities, and a Weak Semantic 3D-CNN based Feature Extraction Backbone (WSFE Module) for classifying shot movement and scale, respectively. Moreover, to support practical cinematographic analysis, we collect FullShots, a large film shot dataset containing 27K shots from 19 movies with professionally annotations for movement and scale information. Following experimental results validate the correctness of our proposed hypotheses, while our framework also outperforms previous methods in terms of accuracy with fewer parameters and computations, on both FullShots and MovieShots datasets. Our code is available at ( https://github.com/litchiar/ShotClassification ).
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2045-2322
Relation: https://doaj.org/toc/2045-2322
DOI: 10.1038/s41598-023-43281-w
URL الوصول: https://doaj.org/article/05fdd3d61e7b4ea584ed1be2fa12e2fe
رقم الأكسشن: edsdoj.05fdd3d61e7b4ea584ed1be2fa12e2fe
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20452322
DOI:10.1038/s41598-023-43281-w