Notice of Violation of IEEE Publication Principles: Motion Vector Estimation of Video Image by Pyramidal Implementation of Lucas Kanade Optical Flow

2009 ◽  
Author(s):  
Sukeshni N. Tamgade ◽  
Vibha R. Bora
Keyword(s):  
Optical Flow ◽  
Motion Vector ◽  
Video Image ◽  
Vector Estimation

A region-based selective optical flow back-projection for genuine motion vector estimation

2007 ◽  
Vol 40 (3) ◽  
pp. 1066-1077 ◽  
Author(s):  
P.-C. Chung ◽  
C.-L. Huang ◽  
E.-L. Chen
Keyword(s):  
Optical Flow ◽  
Motion Vector ◽  
Back Projection ◽  
Vector Estimation

The electronic image stabilization technology research based on improved optical-flow motion vector estimation

2016 ◽  
Author(s):  
Chao Wang ◽  
Ming Ji ◽  
Ying Zhang ◽  
Wentao Jiang ◽  
Xiaoyan Lu ◽  
...  
Keyword(s):  
Optical Flow ◽  
Motion Vector ◽  
Technology Research ◽  
Image Stabilization ◽  
Flow Motion ◽  
Vector Estimation

Motion correction in PET/CT

2005 ◽  
Vol 44 (S 01) ◽  
pp. S46-S50 ◽  
Author(s):  
M. Dawood ◽  
N. Lang ◽  
F. Büther ◽  
M. Schäfers ◽  
O. Schober ◽  
...  
Keyword(s):  
Optical Flow ◽  
Motion Correction ◽  
Motion Vector ◽  
Emission Tomography ◽  
Cardiac Pet ◽  
Novel Approach ◽  
Positron Emission ◽  
Pet Ct ◽  
Flow Algorithm ◽  
Motion Vector Field

Summary:Motion in PET/CT leads to artifacts in the reconstructed PET images due to the different acquisition times of positron emission tomography and computed tomography. The effect of motion on cardiac PET/CT images is evaluated in this study and a novel approach for motion correction based on optical flow methods is outlined. The Lukas-Kanade optical flow algorithm is used to calculate the motion vector field on both simulated phantom data as well as measured human PET data. The motion of the myocardium is corrected by non-linear registration techniques and results are compared to uncorrected images.

An Improved Error Concealment Based on Redundant Motion Vector Information

2012 ◽  
Vol 532-533 ◽  
pp. 1219-1224
Author(s):  
Hong Tao Deng
Keyword(s):  
Video Transmission ◽  
Error Concealment ◽  
Video Quality ◽  
Motion Vector ◽  
Compressed Video ◽  
Vector Information ◽  
Vector Estimation ◽  
Channel Errors ◽  
Bit Stream

During video transmission over error prone network, compressed video bit-stream is sensitive to channel errors that may degrade the decoded pictures severely. In order to solve this problem, error concealment technique is a useful post-processing tool for recovering the lost information. In these methods, how to estimate the lost motion vector correctly is important for the quality of decoded picture. In order to recover the lost motion vector, an Decoder Motion Vector Estimation (DMVE) criterion was proposed and have well effect for recover the lost blocks. In this paper, we propose an improved error concealment method based on DMVE, which exploits the accurate motion vector by using redundant motion vector information. The experimental results with an H.264 codec show that our method improves both subjective and objective decoder reconstructed video quality, especially for sequences of drastic motion.

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