CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 2010 vol.32 Issue No.05 - May
Issue No.05 - May (2010 vol.32)
Jiejie Zhu , University of Central Florida, Orlando
Liang Wang , University of Kentucky, Lexington
Jizhou Gao , University of Kentucky, Lexington
Ruigang Yang , University of Kentucky, Lexington
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2009.68
Time-of-flight range sensors and passive stereo have complimentary characteristics in nature. To fuse them to get high accuracy depth maps varying over time, we extend traditional spatial MRFs to dynamic MRFs with temporal coherence. This new model allows both the spatial and the temporal relationship to be propagated in local neighbors. By efficiently finding a maximum of the posterior probability using Loopy Belief Propagation, we show that our approach leads to improved accuracy and robustness of depth estimates for dynamic scenes.
Stereo, MRFs, time-of-flight sensor, data fusion, global optimization.
Jiejie Zhu, Liang Wang, Jizhou Gao, Ruigang Yang, "Spatial-Temporal Fusion for High Accuracy Depth Maps Using Dynamic MRFs", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.32, no. 5, pp. 899-909, May 2010, doi:10.1109/TPAMI.2009.68