Paper Info
Title
Temporal Shape Super-Resolution by Intra-frame Motion Encoding Using High-fps Structured Light
Abstract
One of the solutions of depth imaging of moving scene is to project a static pattern on the object and use just a single image for reconstruction. However, if the motion of the object is too fast with respect to the exposure time of the image sensor, patterns on the captured image are blurred and reconstruction fails. In this paper, we impose multiple projection patterns into each single captured image to realize temporal super resolution of the depth image sequences. With our method, multiple patterns are projected onto the object with higher fps than possible with a camera. In this case, the observed pattern varies depending on the depth and motion of the object, so we can extract temporal information of the scene from each single image. The decoding process is realized using a learning-based approach where no geometric calibration is needed. Experiments confirm the effectiveness of our method where sequential shapes are reconstructed from a single image. Both quantitative evaluations and comparisons with recent techniques were also conducted.
Year
DOI
Venue
2017
10.1109/ICCV.2017.22
2017 IEEE International Conference on Computer Vision (ICCV)
Keywords
DocType
Volume
intraframe motion encoding,temporal super resolution,single captured image,multiple projection patterns,image sensor,static pattern,depth imaging,high-fps structured light,temporal shape super-resolution,single image,temporal information,observed pattern,multiple patterns,depth image sequences
Conference
abs/1710.00517
Issue
ISSN
ISBN
1
1550-5499
978-1-5386-1033-6
Citations 
PageRank 
References 
0
0.34
20
Authors
5
Name
Order
Citations
PageRank
Yuki Shiba121.05
Satoshi Ono221939.83
ryo furukawa322389.83
Shinsaku Hiura417929.05
hiroshi kawasaki527450.85