In this paper, we present a new method of synthesizing novel views from the virtual cameras in multiview camera configurations for three-dimensional TV (3DTV) system. We introduce a semi-N-view & N-depth framework in order to estimate disparity maps efficiently and correctly. This framework reduces redundancy on disparity estimation by using information from neighboring views. N views can be classified as reference and target images. The disparity maps on the reference images are only estimated by using the cost aggregation method with the weighted least square. The cost functions on the target images are computed by the proposed warping technique so that significant reduction of computation loads is possible. The occlusion problem, which significantly affects the quality of virtual view rendering, is handled by using cost functions computed with multiview images. The proposed method provides a 2D/3D freeview video for 3DTV system. User can select 2D/3D modes of freeview video and control 3D depth perception by adjusting several parameters in 3D freeview video. Experimental results show that the proposed method yields the accurate disparity maps and the synthesized novel view is satisfactory enough to provide seamless freeview videos for 3DTV system.
Bibliographical noteFunding Information:
This work was financially supported by the Ministry of Education, Science and Technology (MEST), the Ministry of Knowledge Economy (MKE) and the Ministry of Labor (MOLAB) through the fostering project of the Lab of Excellency, and was partially supported by the Korea Science and Engineering Foundation (KOSEF) through the Biometrics Engineering Research Center (BERC) at Yonsei University.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering