Visible Persistence is Reduced by Fixed-Trajectory Motion but Not by Random Motion

Perception ◽  
1992 ◽  
Vol 21 (6) ◽  
pp. 791-802 ◽  
Author(s):  
Scott N J Watamaniuk

Despite the sluggish temporal response of the human visual system, moving objects appear clear and without blur, which suggests that visible persistence is reduced when objects move. It has been argued that spatiotemporal proximity alone can account for this modulation of visible persistence and that activation of a motion mechanism per se is not necessary. Experiments are reported which demonstrate that there is a motion-specific influence on visible persistence. Specifically, points moving in constant directions, or fixed trajectories, show less persistence than points moving with the same spatial and temporal displacements but taking random walks, randomly changing direction each frame. Subjects estimated the number of points present in the display for these two types of motion conditions. Under conditions chosen to produce ‘good’ apparent motion, ie small temporal and spatial increments, the apparent number of points for the fixed-trajectory condition was significantly lower than the apparent number in the random-walk condition. The traditional explanation of the suppression of persistence based on the spatiotemporal proximity of objects cannot account for these results. The enhanced suppression of persistence observed for a target moving in a consistent direction depends upon the activation of a directionally tuned motion mechanism extended over space and time.

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 1965
Author(s):  
Juncai Zhu ◽  
Zhizhong Wang ◽  
Songwei Wang ◽  
Shuli Chen

Detecting moving objects in a video sequence is an important problem in many vision-based applications. In particular, detecting moving objects when the camera is moving is a difficult problem. In this study, we propose a symmetric method for detecting moving objects in the presence of a dynamic background. First, a background compensation method is used to detect the proposed region of motion. Next, in order to accurately locate the moving objects, we propose a convolutional neural network-based method called YOLOv3-SOD for detecting all objects in the image, which is lightweight and specifically designed for small objects. Finally, the moving objects are determined by fusing the results obtained by motion detection and object detection. Missed detections are recalled according to the temporal and spatial information in adjacent frames. A dataset is not currently available specifically for moving object detection and recognition, and thus, we have released the MDR105 dataset comprising three classes with 105 videos. Our experiments demonstrated that the proposed algorithm can accurately detect moving objects in various scenarios with good overall performance.


1987 ◽  
Vol 24 (02) ◽  
pp. 315-327
Author(s):  
Enzo Orsingher

In this paper a random motion on the surface of the 3-sphere whose probability law is a solution of the telegraph equation in spherical coordinates is presented. The connection of equations governing the random motion with Maxwell equations is examined together with some qualitative features of its sample paths. Finally Brownian motion on the 3-sphere is derived as the limiting process of a random walk with latitude-changing probabilities.


2017 ◽  
Vol 5 (36) ◽  
pp. 7491-7495 ◽  
Author(s):  
Ross W. Jaggers ◽  
Stefan A. F. Bon

A spatial and temporal response of hydrogel objects is demonstrated using an enzyme as a programming tool.


1987 ◽  
Vol 24 (2) ◽  
pp. 315-327 ◽  
Author(s):  
Enzo Orsingher

In this paper a random motion on the surface of the 3-sphere whose probability law is a solution of the telegraph equation in spherical coordinates is presented. The connection of equations governing the random motion with Maxwell equations is examined together with some qualitative features of its sample paths. Finally Brownian motion on the 3-sphere is derived as the limiting process of a random walk with latitude-changing probabilities.


Author(s):  
MARTIN BURGER ◽  
JAN-FREDERIK PIETSCHMANN ◽  
HELENE RANETBAUER ◽  
CHRISTIAN SCHMEISER ◽  
MARIE-THERESE WOLFRAM

In this paper, we derive and analyse mean-field models for the dynamics of groups of individuals undergoing a random walk. The random motion of individuals is only influenced by the perceived densities of the different groups present as well as the available space. All individuals have the tendency to stay within their own group and avoid the others. These interactions lead to the formation of aggregates in case of a single species and to segregation in the case of multiple species. We derive two different mean-field models, which are based on these interactions and weigh local and non-local effects differently. We discuss existence and stability properties of solutions for both models and illustrate the rich dynamics with numerical simulations.


2015 ◽  
Vol 87 (3) ◽  
pp. 249-259 ◽  
Author(s):  
Deepak S. Patil ◽  
Manisha S. Konale ◽  
Jakub Kolar ◽  
Koichi Shimakawa ◽  
Vitezslav Zima ◽  
...  

AbstractElectrical properties of a set of lithium-ion conducting sulfide glasses with general formula 20LiI-xGa2S3-(80-x)GeS2 (x = 10, 15 and 20) is studied in the present article. The experimental data obtained using impedance spectroscopy are analyzed by means of a random-walk (RW) model assuming that the conduction takes place by a random motion of Li+ ions. The influences of added gallium on the structural network and on the conductivity of prepared glasses are also analyzed using the RW model. The results are further confirmed by Raman spectral analysis. The results obtained by the random-walk model and by a conventional equivalent electric circuit model are in a good agreement. We observed that the addition of Ga2S3 contributed to phase separation in the prepared glassy system and negatively influenced the conductivity of the studied glasses. Factors contributing to the total conductivity with respect to the amount of both LiI and Ga2S3 are also reported.


2020 ◽  
Vol 9 (9) ◽  
pp. 555
Author(s):  
Deepak Elias ◽  
Bart Kuijpers

Space–time prisms are used to model the uncertainty of space–time locations of moving objects between (for instance, GPS-measured) sample points. However, not all space–time points in a prism are equally likely and we propose a simple, formal model for the so-called “visit probability” of space–time points within prisms. The proposed mathematical framework is based on a binomial random walk within one- and two-dimensional space–time prisms. Without making any assumptions on the random walks (we do not impose any distribution nor introduce any bias towards the second anchor point), we arrive at the conclusion that binomial random walk-based visit probability in space–time prisms corresponds to a hypergeometric distribution.


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