3-D motion and shape from multiple image sequences

2004 ◽  
Author(s):  
R. Mecke ◽  
B. Michaelis
Keyword(s):  
Image Sequences ◽  
Multiple Image

Removal of Moving Objects from a Street-View Image by Fusing Multiple Image Sequences

2010 ◽  
Author(s):  
Hiroyuki Uchiyama ◽  
Daisuke Deguchi ◽  
Tomokazu Takahashi ◽  
Ichiro Ide ◽  
Hiroshi Murase
Keyword(s):  
Moving Objects ◽  
Image Sequences ◽  
Multiple Image ◽  
Street View

3D model-based tracking of human actions from multiple image sequences

1998 ◽  
Vol 29 (8) ◽  
pp. 48-56
Author(s):  
Akitsugu Sato ◽  
Satoshi Kawada ◽  
Yoshihiko Osaki ◽  
Masanobu Yamamoto
Keyword(s):  
3D Model ◽  
Image Sequences ◽  
Human Actions ◽  
Multiple Image ◽  
Model Based

Computer processing of high-resolution images of periodic specimens

1986 ◽  
Vol 44 ◽  
pp. 2-5
Author(s):  
W. Chiu ◽  
M.F. Schmid ◽  
T.-W. Jeng
Keyword(s):  
High Resolution ◽  
Fourier Transforms ◽  
Complex Structure ◽  
Distribution Functions ◽  
Multiple Image ◽  
Cryo Electron Microscopy ◽  
Structure Factors ◽  
Unit Cells ◽  
High Resolution Images ◽  
Phase Probability Distribution

Cryo-electron microscopy has been developed to the point where one can image thin protein crystals to 3.5 Å resolution. In our study of the crotoxin complex crystal, we can confirm this structural resolution from optical diffractograms of the low dose images. To retrieve high resolution phases from images, we have to include as many unit cells as possible in order to detect the weak signals in the Fourier transforms of the image. Hayward and Stroud proposed to superimpose multiple image areas by combining phase probability distribution functions for each reflection. The reliability of their phase determination was evaluated in terms of a crystallographic “figure of merit”. Grant and co-workers used a different procedure to enhance the signals from multiple image areas by vector summation of the complex structure factors in reciprocal space.

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