Title :
Depth map estimation from motion for 2D to 3D conversion
Author :
Liu, Chao ; Christopher, Lauren
Author_Institution :
Dept. of Electr. & Comput. Eng., Indiana Univ. Purdue Univ. Indianapolis, Indianapolis, IN, USA
Abstract :
The conversion of existing 2D videos to 3D videos is an important process for 3D video production. Generating an accurate depth map is the key starting pointfor this 2D to 3D conversion. This paper presents a novel method for generating the depth map of 2D image sequences from motion information. Different from the typical multi-view stereo method, this approach calculates the motion information directly from two sequential images which are captured by only a single moving camera. Classical constrained optical flow is known to be inaccurate for textureless regions and complicated areas. Our new approach uses mean shift segmentation algorithm and optical flow together to compute the depth map. The motion-based depth map and the segmented map are integrated into one depth map using breadth-first search methods. We find improved results compared to the optical flow method.
Keywords :
image motion analysis; image segmentation; image sequences; tree searching; video signal processing; 2D image sequences; 2D videos; 3D videos; breadth-first search methods; classical constrained optical flow; depth map estimation; mean shift segmentation algorithm; motion information; motion-based depth map; multi-view stereo method; single moving camera; Cameras; Computer vision; Image motion analysis; Image segmentation; Optical filters; Optical imaging; Three dimensional displays; 3D; depth; segmentation;
Conference_Titel :
Electro/Information Technology (EIT), 2012 IEEE International Conference on
Conference_Location :
Indianapolis, IN
Print_ISBN :
978-1-4673-0819-9
DOI :
10.1109/EIT.2012.6220749