Deep-Learning-Based Motion Capture Technology in Film and Television Animation Production. (11th February 2022)
- Record Type:
- Journal Article
- Title:
- Deep-Learning-Based Motion Capture Technology in Film and Television Animation Production. (11th February 2022)
- Main Title:
- Deep-Learning-Based Motion Capture Technology in Film and Television Animation Production
- Authors:
- Wei, Yating
- Other Names:
- Chen Chin-Ling Academic Editor.
- Abstract:
- Abstract : With the popularity of King Kong, Pirates of the Caribbean 2, Avatar, and other films, the virtual characters in these films have become popular and well loved by audiences. The creation of these virtual characters is different from traditional 3D animation but is based on real character movements and expressions. An overview of several mainstream motion capture systems in the field of motion capture is presented, and the application of motion capture technology in film and animation is explained in detail. The current motion capture technology is mainly based on complex human markers and sensors, which are costly, while deep-learning-based human pose estimation is becoming a new option. However, most existing methods are based on a single person or picture estimation, and there are many challenges for video multiperson estimation. The experimental results show that a simple design of the human motion capture system is achieved.
- Is Part Of:
- Security and communication networks. Volume 2022(2022)
- Journal:
- Security and communication networks
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-02-11
- Subjects:
- Computer networks -- Security measures -- Periodicals
Computer security -- Periodicals
Cryptography -- Periodicals
005.805 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1939-0122 ↗
https://www.hindawi.com/journals/scn/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1155/2022/6040371 ↗
- Languages:
- English
- ISSNs:
- 1939-0114
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 21128.xml