© The Institution of Engineering and Technology
2D-to-3D conversion has been studied over past decades and integrated to commercial 3D displays and 3DTVs. Generally, depth cues extracted from a static image are used for generating a depth map followed by depth image-based rendering for producing a stereoscopic image. Further, the motion has been considered as an important cue for motion depth estimation. In most works, motion estimation has relied on block-based motion estimation, optical flows, and their variants even though they provide inaccurate data and high computation time, posing performance bottleneck. These problems by proposing Motion History Image-based motion depth estimation method are addressed. Experimental results show that the proposed method is not only faster than the conventional methods but also outperforms them in terms of motion depth estimation.
References
-
-
1)
-
1. Po, L., Xu, X., Zhu, Y., et al: ‘Automatic 2D-to-3D video conversion technique based on depth-from motion and color segmentation’. IEEE Int. Conf. Signal Processing, Beijing, China, 2010, pp. 1000–1003.
-
2)
-
2. Konrad, J., Wang, F., Ishwar, P., et al: ‘Learning-based, automatic 2D-to-3D image and video conversion’, Trans. Image Process., 2013, 22, (9), pp. 3485–3496 (doi: 10.1109/TIP.2013.2270375).
-
3)
-
7. Tsia, D., Flagg, M., Rehg, J.: ‘Motion coherent tracking with multi-label MRF optimization’. Proc. British Machine Vision Conf., Aberystwyth, UK, September 2010.
-
4)
-
3. Kim, D., Min, D., Sohn, K.: ‘A stereoscopic video generation method using stereoscopic display characterization and motion analysis’, Trans. Broadcast., 2008, 54, (2), pp. 188–197 (doi: 10.1109/TBC.2007.914714).
-
5)
-
52. Bobick, A.F., Davies, J.: ‘The recognition of human movement using temporal templates’, IEEE T. Pattern Anal., 2001, 23, (3), pp. 257–267, (doi: 10.1109/34.910878).
-
6)
-
4. Xu, F., Er, G., Xie, X., et al: ‘2D-to-3D conversion based on motion and color mergence’. 3DTV Conf.: The True Vision – Capture, Transmission and Display of 3D Video, Istanbul, Turkey, 2008, pp. 205–208.
-
7)
-
6. Fukuchi, K., Miyazato, K., Kimura, A., et al: ‘Saliency-based video segmentation with graph cuts and sequentially updated priors’. IEEE Int. Conf. Multi Expo, New York, USA, June–July 2009, pp. 638–641.
http://iet.metastore.ingenta.com/content/journals/10.1049/el.2017.1505
Related content
content/journals/10.1049/el.2017.1505
pub_keyword,iet_inspecKeyword,pub_concept
6
6