TY - GEN
T1 - Creating multi-viewpoint panoramas of streets with sparsely located buildings
AU - Okatani, Takayuki
AU - Yanagisawa, Jun
AU - Tetsuka, Daiki
AU - Sakurada, Ken
AU - Deguchi, Koichiro
PY - 2014
Y1 - 2014
N2 - This paper presents a method for creating multi-viewpoint panoramas that is particularly targeted at streets with sparsely located buildings. As is known in the literature, it is impossible to create panoramas of such scenes having a wide range of depths in a distortion-free manner. To overcome this difficulty, our method renders sharp images only for the facades of buildings and the ground surface (e.g., vacant lands and sidewalks) along the target streets; it renders blurry images for other objects in the scene to make their geometric distortion less noticeable while maintaining their presence. To perform these, our method first estimates the three-dimensional structures of the target scenes using the results obtained by SfM (structure from motion), identifies to which category (i.e., the facade surface, the ground surface, or other objects) each scene point belongs based on MRF (Markov Random Field) optimization, and creates panoramic images of the scene by mosaicing the images of the three categories. The blurry images of objects are generated by a similar technique to digital refocus of the light field photography. We present several panoramic images created by our method for streets in the tsunami-devastated areas in the north-eastern Japan coastline because of the Great East Japan Earthquake of March 11, 2011.
AB - This paper presents a method for creating multi-viewpoint panoramas that is particularly targeted at streets with sparsely located buildings. As is known in the literature, it is impossible to create panoramas of such scenes having a wide range of depths in a distortion-free manner. To overcome this difficulty, our method renders sharp images only for the facades of buildings and the ground surface (e.g., vacant lands and sidewalks) along the target streets; it renders blurry images for other objects in the scene to make their geometric distortion less noticeable while maintaining their presence. To perform these, our method first estimates the three-dimensional structures of the target scenes using the results obtained by SfM (structure from motion), identifies to which category (i.e., the facade surface, the ground surface, or other objects) each scene point belongs based on MRF (Markov Random Field) optimization, and creates panoramic images of the scene by mosaicing the images of the three categories. The blurry images of objects are generated by a similar technique to digital refocus of the light field photography. We present several panoramic images created by our method for streets in the tsunami-devastated areas in the north-eastern Japan coastline because of the Great East Japan Earthquake of March 11, 2011.
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U2 - 10.1007/978-3-642-40686-7_5
DO - 10.1007/978-3-642-40686-7_5
M3 - Conference contribution
AN - SCOPUS:84897694378
SN - 9783642406850
T3 - Springer Tracts in Advanced Robotics
SP - 65
EP - 79
BT - Field and Service Robotics - Results of the 8th International Conference
T2 - 8th International Conference on Field and Service Robotics, FSR 2012
Y2 - 16 July 2012 through 19 July 2012
ER -