Thesis
HANDiMATE: digital puppeteering using a hand depth sensor for animation
Master of Science (M.S.), Drexel University
Jun 2022
DOI:
https://doi.org/10.17918/00001109
Abstract
This project seeks to identify an effective animation input method that is more intuitive, quicker, and less expensive than the industry-standard 3D animation input methods. The HANDiMATE input method was innovated using Unreal Engine and a leap motion sensor to act as a minimal viable product as a hand depth sensor-driven character animation input method. This study found that the advantages of HANDiMATE outweighed the disadvantages, according to participants. 93% percent of participants believed HANDiMATE could be a useful tool for creating character animations quickly with a portion of those participants citing minor to significant changes to make HANDiMATE more viable. Furthermore, many participants enjoyed the process of using HANDiMATE and many felt encouraged to practice using the input method to get better. The results show that a hand depth sensor-based animation input for character animation could be a substitution for current input methods with the right tools and practice using the input method.
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Details
- Title
- HANDiMATE
- Creators
- Alexus Aiken
- Contributors
- Nicholas E. Jushchyshyn (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Master of Science (M.S.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- vi, 46 pages
- Resource Type
- Thesis
- Language
- English
- Academic Unit
- Digital Media; Drexel University; Antoinette Westphal College of Media Arts and Design
- Other Identifier
- 991018528010804721