scholarly journals 3D motion direction estimation
 – Model predictions and data

2018 ◽  
Vol 18 (10) ◽  
pp. 130
Author(s):  
Kathryn Bonnen ◽  
Thaddeus Czuba ◽  
Jake Whritner ◽  
Austin Kuo ◽  
Alexander Huk ◽  
...  
2013 ◽  
Vol 846-847 ◽  
pp. 1106-1110
Author(s):  
Guo Qing Yang ◽  
Rong Yi Cui

Taking the wavelet decomposed approximate image as the main research object, a direction estimation method for moving object was proposed in this paper. Firstly, the approximate image for the frame of the video was obtained via wavelet decomposition; and furthermore, the motion estimation on the approximate image was achieved to obtain the motion vectors. Finally, the motion vectors were described as polar coordinate form to compute the number of motion vectors in specified angles and the information entropy of the motion directions. The experiment results show that the proposed method can remove the effect of noise and the results of direction estimation are consistent with the actual motion directions.


Vision ◽  
2019 ◽  
Vol 3 (4) ◽  
pp. 64
Author(s):  
Martin Lages ◽  
Suzanne Heron

Like many predators, humans have forward-facing eyes that are set a short distance apart so that an extensive region of the visual field is seen from two different points of view. The human visual system can establish a three-dimensional (3D) percept from the projection of images into the left and right eye. How the visual system integrates local motion and binocular depth in order to accomplish 3D motion perception is still under investigation. Here, we propose a geometric-statistical model that combines noisy velocity constraints with a spherical motion prior to solve the aperture problem in 3D. In two psychophysical experiments, it is shown that instantiations of this model can explain how human observers disambiguate 3D line motion direction behind a circular aperture. We discuss the implications of our results for the processing of motion and dynamic depth in the visual system.


2014 ◽  
Vol 513-517 ◽  
pp. 3224-3227
Author(s):  
Yu Jie Liu

The paper mainly discusses the emergency evacuation when group incident occurs. In crowded areas, group incidents will result in disorder of flow information, nonlinear and catastrophe of flow density and motion direction. The traditional evacuation route guidance only selects evacuation route for orderly, smooth flow density variations, in which nonlinearity and mutation of the flow information cannot be reflected. Therefore, once the Group incidents occurred, the stability of the model will be destroyed. To solve the problem, the paper proposes an emergency evacuation method based on path collision probability estimation model. Simulation results show that this algorithm can improve the speed of evacuation.


2010 ◽  
Vol 9 (8) ◽  
pp. 637-637 ◽  
Author(s):  
S. Heron ◽  
M. Lages
Keyword(s):  

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