In this paper, we present an efficient method to synthesize large-scale scenes, such as broad city landscapes. To date, model based approaches have mainly been adopted for this purpose, and some fairly convincing polygon cities have been successfully generated However, the shapes of real world objects are usually very complicated and it is infeasible to model an entire city realistically. On the other hand, image based approaches have been attempted only recently. Image based methods are effective for realistic rendering, but their huge data sets and restrictions on interactivity pose serious problems for an actual application. Thus, we propose a hybrid method, which uses simple shapes such as planes to model the city, and applies image based techniques to acid realism. It can be performed automatically through a simple image capturing process. Further We also analyze the relationship between error and number of needed images to reduce the data size.
|Journal||Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition|
|Publication status||Published - Dec 1 2001|
|Event||2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Kauai, HI, United States|
Duration: Dec 8 2001 → Dec 14 2001
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition