Images, Imagination, and Movement: Pictorial Representations and Their Development in the Work of James Gibson

Perception ◽  
10.1068/p2976 ◽  
2000 ◽  
Vol 29 (6) ◽  
pp. 635-648 ◽  
Author(s):  
James E Cutting
Keyword(s):  
Vector Field ◽  
Optical Flow ◽  
Spherical Representation ◽  
Pictorial Representations ◽  
The Relationship

For more than 30 years James Gibson studied pictures and he studied motion, particularly the relationship between movement through an environment and its visual consequences. For the latter, he also struggled with how best to present his ideas to students and fellow researchers, and employed various representations and formats. This article explores the relationships between the concepts of the fidelity of pictures (an idea he first promoted and later eschewed) and evocativeness as applied to his images. Gibson ended his struggle with an image of a bird flying over a plane surrounded by a spherical representation of a vector field, an image high in evocativeness but less than completely faithful to optical flow.

Some Properties of Symplectic Manifolds S on the Projective Tangent Bundle PTM

2011 ◽  
Vol 187 ◽  
pp. 483-486
Author(s):  
Yong He ◽  
Xiao Ying Lu ◽  
Wei Na Lu
Keyword(s):  
Vector Field ◽  
Symplectic Manifold ◽  
Tangent Bundle ◽  
Fiber Bundle ◽  
Symplectic Manifolds ◽  
Lie Derivative ◽  
The Relationship

In this paper, we show the relationship between 2-form of the two projective tangent bundle and the relationship between 2-form on projective tangent bundle and 1-form on by using the theory of fiber bundle and the properties of symplectic manifold of the projective tangent bundle . Moreover, we derived a simpler formula of Lie derivative of a special vector field, which is on the projective tangent bundle.

Relationships between Head-Shoulder Divergences and Sickness in a Virtual Environment

1998 ◽  
Vol 42 (21) ◽  
pp. 1471-1475 ◽  
Author(s):  
Jennifer A. Ehrlich ◽  
Michael J. Singer ◽  
Robert C. Allen
Keyword(s):  
Optical Flow ◽  
Virtual Environments ◽  
Virtual Environment ◽  
Flow Patterns ◽  
Time On Task ◽  
The Relationship

Sickness is often experienced during exposure to virtual environments (VEs). Optical flow patterns may influence this VE sickness. We investigated the relationship between VE sickness and head-shoulder divergence angles while moving through a VE. The VE experience induced some level of VE sickness in all participants. Those not completing the study evidenced significantly more severe VE sickness symptoms than those completing it did. No relationships between head-shoulder divergence and sickness were revealed for experimental dropouts. However, significant correlations were found between several sickness measures and head-shoulder divergences for those completing the study. An interaction between head-shoulder divergence and time on task may exist.

scholarly journals Motion Vector Field Estimation Using Brightness Constancy Assumption and Epipolar Geometry Constraint

2014 ◽  
Vol II-1 ◽  
pp. 9-16 ◽  
Author(s):  
S. Hosseinyalamdary ◽  
A. Yilmaz
Keyword(s):  
Vector Field ◽  
Optical Flow ◽  
Motion Vector ◽  
Epipolar Geometry ◽  
Estimation Methods ◽  
Brightness Constancy ◽  
Flow Estimation ◽  
Optical Flow Estimation ◽  
Motion Vector Field ◽  
Field Estimation

In most Photogrammetry and computer vision tasks, finding the corresponding points among images is required. Among many, the Lucas-Kanade optical flow estimation has been employed for tracking interest points as well as motion vector field estimation. This paper uses the IMU measurements to reconstruct the epipolar geometry and it integrates the epipolar geometry constraint with the brightness constancy assumption in the Lucas-Kanade method. The proposed method has been tested using the KITTI dataset. The results show the improvement in motion vector field estimation in comparison to the Lucas-Kanade optical flow estimation. The same approach has been used in the KLT tracker and it has been shown that using epipolar geometry constraint can improve the KLT tracker. It is recommended that the epipolar geometry constraint is used in advanced variational optical flow estimation methods.

On smoothness of a vector field-application to optical flow

1988 ◽  
Vol 10 (6) ◽  
pp. 943-949 ◽  
Author(s):  
A. Mitiche ◽  
R. Grisell ◽  
J.K. Aggarwal
Keyword(s):  
Vector Field ◽  
Optical Flow ◽  
Field Application

Rigidity and concircular symmetries

2021 ◽  
pp. 2150202
Author(s):  
Andrés Franco
Keyword(s):  
Vector Field ◽  
Vector Fields ◽  
Lorentzian Geometry ◽  
Rigidity Result ◽  
The Relationship

We present a rigidity result in Lorentzian geometry, related to Bartnik’s conjecture, under the hypothesis of the existence of a concircular vector field with certain properties. We also study the relationship between two different notions of concircular vector fields found in the literature, and give conditions for a generalized Robertson–Walker spacetime to have a timelike concircular vector field.

TOPOLOGICAL STRUCTURE OF ENTROPY OF (3+1)-DIMENSIONAL SPHERICALLY SYMMETRIC BLACK HOLES

2001 ◽  
Vol 16 (22) ◽  
pp. 1457-1464 ◽  
Author(s):  
GUO-HONG YANG
Keyword(s):  
Black Holes ◽  
Vector Field ◽  
Physical Meaning ◽  
Topological Structure ◽  
Killing Vector ◽  
Entropy Density ◽  
Topological Invariants ◽  
Spherically Symmetric ◽  
Killing Vector Field ◽  
The Relationship

Using the relationship between the entropy and the Euler characteristic, an entropy density is introduced to describe the inner topological structure of the entropy of (3+1)-dimensional spherically symmetric black holes. It is pointed out that the density of entropy is determined by the singularities of the timelike Killing vector field of space–time, and these singularities carry the topological numbers, Hopf indices and Brouwer degrees, naturally, which are topological invariants. Taking account of the physical meaning in statistics, the entropy of black holes is given by the Hopf indices merely, which will lead to the increasing principle of entropy of black holes.

Vector-Field dynamic X-ray (VF-DXR) using Optical Flow Method

2021 ◽  
pp. 20201210
Author(s):  
Takuya Hino ◽  
Akinori Tsunomori ◽  
Takenori Fukumoto ◽  
Akinori Hata ◽  
Masako Ueyama ◽  
...  
Keyword(s):  
Vector Field ◽  
Optical Flow ◽  
Color Coding ◽  
X Ray ◽  
Flow Method ◽  
Optical Flow Method ◽  
Copd Patients ◽  
Vector Projection ◽  
Field Dynamic ◽  
Pixel Value

Objectives: To explore the feasibility of Vector-Field DXR (VF-DXR) using optical flow method (OFM). Methods: Five healthy volunteers and five COPD patients were studied. DXR was performed in the standing position using a prototype X-ray system (Konica Minolta Inc., Tokyo, Japan). During the examination, participants took several tidal breaths and one forced breath. DXR image file was converted to the videos with different frames per second (fps): 15 fps, 7.5 fps, five fps, three fps, and 1.5 fps. Pixel-value gradient was calculated by the serial change of pixel value, which was subsequently converted mathematically to motion vector using OFM. Color-coding map and vector projection into horizontal and vertical components were also tested. Results: Dynamic motion of lung and thorax was clearly visualized using VF-DXR with an optimal frame rate of 5 fps. Color-coding map and vector projection into horizontal and vertical components were also presented. VF-DXR technique was also applied in COPD patients. Conclusion: The feasibility of VF-DXR was demonstrated with small number of healthy subjects and COPD patients. Advances in knowledge: A new Vector-Field Dynamic X-ray (VF-DXR) technique is feasible for dynamic visualization of lung, diaphragms, thoracic cage, and cardiac contour.

Adapted Approach for Omnidirectional Egomotion Estimation

2013 ◽  
pp. 1-13
Author(s):  
A. Radgui ◽  
C. Demonceaux ◽  
E. Mouaddib ◽  
M. Rziza ◽  
D. Aboutajdine
Keyword(s):  
Optical Flow ◽  
Experimental Results ◽  
Motion Field ◽  
Camera Motion ◽  
Spherical Representation ◽  
Estimation Process ◽  
Error Measures ◽  
Egomotion Estimation ◽  
Omnidirectional Image ◽  
Omnidirectional Images

Egomotion estimation is based principally on the estimation of the optical flow in the image. Recent research has shown that the use of omnidirectional systems with large fields of view allow overcoming the limitation presented in planar-projection imagery in order to address the problem of motion analysis. For omnidirectional images, the 2D motion is often estimated using methods developed for perspective images. This paper adapts motion field calculated using adapted method which takes into account the distortions existing in the omnidirectional image. This 2D motion field is then used as input to the egomotion estimation process using spherical representation of the motion equation. Experimental results are shown and comparison of error measures are given to confirm that succeeded estimation of camera motion will be obtained when using an adapted method to estimate optical flow.

Visual Perception of Three-Dimensional Motion

1990 ◽  
Vol 2 (2) ◽  
pp. 129-137 ◽  
Author(s):  
David J. Heeger ◽  
Allan Jepson
Keyword(s):  
Flow Field ◽  
Optical Flow ◽  
Visual Stimulation ◽  
Rotational Velocity ◽  
Three Dimensional ◽  
Algebraic Manipulation ◽  
Difficult Problem ◽  
3D Motion ◽  
Optical Flow Field ◽  
The Relationship

As an observer moves and explores the environment, the visual stimulation in his eye is constantly changing. Somehow he is able to perceive the spatial layout of the scene, and to discern his movement through space. Computational vision researchers have been trying to solve this problem for a number of years with only limited success. It is a difficult problem to solve because the relationship between the optical-flow field, the 3D motion parameters, and depth is nonlinear. We have come to understand that this nonlinear equation describing the optical-flow field can be split by an exact algebraic manipulation to yield an equation that relates the image velocities to the translational component of the 3D motion alone. Thus, the depth and the rotational velocity need not be known or estimated prior to solving for the translational velocity. The algorithm applies to the general case of arbitrary motion with respect to an arbitrary scene. It is simple to compute and it is plausible biologically.

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