CANavi: Synthesizing Cartoon-Like Animation for Street Navigation Based on Google Maps

Autor:	Lieu-Hen Chen, Hao-Ming Hung, Yasufumi Takama, Eric Hsiao-Kuang Wu, Cheng-Yu Sun
Rok vydání:	2021
Předmět:	Human–computer interaction Computer science Mechanical Engineering Perception media_common.quotation_subject Automotive Engineering Animation Software walkthrough Computer animation Computer Science Applications media_common
Zdroj:	IEEE Intelligent Transportation Systems Magazine. 13:227-238
ISSN:	1941-1197 1939-1390
DOI:	10.1109/mits.2019.2953545
Popis:	Today, Google Maps has become one of the most important tools for exploring maps. In addition, Google Street View further provides images for improving users’ cognition of new smart cities. Many route recommendation services are available online, but most provide recommended routes on a 2D planar map. This can create a gap between a user’s perception and reality. It is not easy for users to understand an unfamiliar place through linked line-segments on a 2D map only. Many users find themselves lost while they attempt to virtually walkthrough an area in Google Street View via a mouse. Moreover, these street images are static and do not depict current weather conditions. Therefore, in this paper, we propose a novel approach for synthesizing cartoon-like animation for street navigation (CANavi). To achieve our goal, we utilized the abundant resources from Google Maps and Google Street View. The results show that our street-navigation animations create interesting and vivid sceneries that can successfully improve a user’s cognition and experience when exploring new smart cities.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::bfea8ff4a90132855b13e26d0008aa54 https://doi.org/10.1109/mits.2019.2953545 Zobrazit plný text záznamu