Silhouettes from Real Objects Enable Realistic Interactions with a Virtual Human in Mobile Augmented Reality

Title
Silhouettes from Real Objects Enable Realistic Interactions with a Virtual Human in Mobile Augmented Reality
Authors
황재인김한섭가잔파 알리안드레아스 패스토이명호김정현
Keywords
augmented reality; mobile AR; deep learning; segmentation; realistic interaction
Issue Date
2021-03
Publisher
Applied Sciences-basel
Citation
VOL 11, 2763
Abstract
Realistic interactions with real objects (e.g., animals, toys, robots) in an augmented reality (AR) environment enhances the user experience. The common AR apps on the market achieve realistic interactions by superimposing pre-modeled virtual proxies on the real objects in the AR environment. This way user perceives the interaction with virtual proxies as interaction with real objects. However, catering to environment change, shape deformation, and view update is not a trivial task. Our proposed method uses the dynamic silhouette of a real object to enable realistic interactions. Our approach is practical, lightweight, and requires no additional hardware besides the device camera. For a case study, we designed a mobile AR application to interact with real animal dolls. Our scenario included a virtual human performing four types of realistic interactions. Results demonstrated our method’s stability that does not require pre-modeled virtual proxies in case of shape deformation and view update. We also conducted a pilot study using our approach and reported significant improvements in user perception of spatial awareness and presence for realistic interactions with a virtual human.
URI
http://pubs.kist.re.kr/handle/201004/73012
ISSN
2076-3417
Appears in Collections:
KIST Publication > Article
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