Technology Transfer: From the Film Industry to Architecture

García, Federico Luis del Blanco; Ríos, Ismael García

doi:10.1007/978-3-319-58856-8_9

Cited by 1 publication

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“…The most common types of computer applications used in matte painting are 2D, 2.5D, and 3D ( Eisenmann and Parent 2010 ). Using 2D technology, it is possible to generate backgrounds such as grand mountains or skies by arranging digital images on a flat surface ( del Blanco García and García Ríos 2017 ). With 2.5D technology, multiple images are layered at multiple depths in a picture, creating an enhanced image.…”

Section: Literature Reviewmentioning

confidence: 99%

Examining the Influence of Using First-Person View Drones as Auxiliary Devices in Matte Painting Courses on College Students’ Continuous Learning Intention

Sun

Chen

et al. 2022

J. Intell.

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In terms of the teaching process of matte painting, it is essential for students to develop a sound understanding of the relationship between virtual and physical environments. In this study, first-person view (FPV) drones are applied to matte painting courses to evaluate the effectiveness of the teaching, and to propose more effective design suggestions for FPV drones that are more suitable for teaching. This provides students with a better learning environment using a digital education system. The results of the study indicate that the flow experience, learning interest, and continuous learning intention of students who use FPV drones in matte painting are significantly greater than those of students who only utilize traditional teaching methods. Furthermore, the technology incentive model (TIM) was developed in this study after being verified by the structural equation model. The results demonstrate that the second-order construct ‘technology incentive’ comprising perceived interactivity, perceived vividness, and novel experience positively influence students’ learning interest and continuous learning intentions under the mediation of flow experience.

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Section: Literature Reviewmentioning

confidence: 99%