scholarly journals Contour shape effects on search performance: evidence for constant curvature coding

2010 ◽  
Vol 5 (8) ◽  
pp. 468-468
Author(s):  
P. Garrigan ◽  
P. J. Kellman
Keyword(s):  
Constant Curvature ◽  
Search Performance ◽  
Contour Shape ◽  
Shape Effects

The Role of Constant Curvature in 2-D Contour Shape Representations

Perception ◽  
10.1068/p6970 ◽  
2011 ◽  
Vol 40 (11) ◽  
pp. 1290-1308 ◽  
Author(s):  
Patrick Garrigan ◽  
Philip J Kellman
Keyword(s):  
Retention Interval ◽  
Constant Curvature ◽  
Visual Information ◽  
Recognition Performance ◽  
Shape Representations ◽  
Contour Shape ◽  
Position And Orientation ◽  
Retention Intervals ◽  
Invariant Shape

In early cortex, visual information is encoded by retinotopic orientation-selective units. Higher-level representations of abstract properties, such as shape, require encodings that are invariant to changes in size, position, and orientation. Within the domain of open, 2-D contours, we consider how an economical representation that supports viewpoint-invariant shape comparisons can be derived from early encodings. We explore the idea that 2-D contour shapes are encoded as joined segments of constant curvature. We report three experiments in which participants compared sequentially presented 2-D contour shapes comprised of constant curvature (CC) or non-constant curvature (NCC) segments. We show that, when shapes are compared across viewpoint or for a retention interval of 1000 ms, performance is better for CC shapes. Similar recognition performance is observed for both shape types, however, if they are compared at the same viewpoint and the retention interval is reduced to 500 ms. These findings are consistent with a symbolic encoding of 2-D contour shapes into CC parts when the retention intervals over which shapes must be stored exceed the duration of initial, transient, visual representations.

scholarly journals Constant Curvature Parts-Based Representation of Contour Shape

2011 ◽  
Vol 11 (11) ◽  
pp. 1098-1098
Author(s):  
P. Garrigan ◽  
P. Kellman
Keyword(s):  
Constant Curvature ◽  
Contour Shape

scholarly journals Constant Curvature Representations of Contour Shape

2019 ◽  
Vol 19 (10) ◽  
pp. 94
Author(s):  
Nicholas Baker ◽  
Philip J. Kellman
Keyword(s):  
Constant Curvature ◽  
Contour Shape

Multislice calculations for quasi-periodic and non-periodic objects

1990 ◽  
Vol 48 (4) ◽  
pp. 138-139
Author(s):  
R. Herrera ◽  
A. Gómez
Keyword(s):  
Electron Diffraction ◽  
Computer Simulations ◽  
Periodic Table ◽  
Amorphous Materials ◽  
Space Group ◽  
Essential Step ◽  
Shape Effects ◽  
Atomic Scattering ◽  
Diffraction Patterns ◽  
Periodic Continuation

Computer simulations of electron diffraction patterns and images are an essential step in the process of structure and/or defect elucidation. So far most programs are designed to deal specifically with crystals, requiring frequently the space group as imput parameter. In such programs the deviations from perfect periodicity are dealt with by means of “periodic continuation”.However, for many applications involving amorphous materials, quasiperiodic materials or simply crystals with defects (including finite shape effects) it is convenient to have an algorithm capable of handling non-periodicity. Our program “HeGo” is an implementation of the well known multislice equations in which no periodicity assumption is made whatsoever. The salient features of our implementation are: 1) We made Gaussian fits to the atomic scattering factors for electrons covering the whole periodic table and the ranges [0-2]Å−1 and [2-6]Å−1.

The Influences of Goal and Laterality of a Prepared Hand Response on a Co-Occurring Visual Search

2015 ◽  
Vol 74 (1) ◽  
pp. 55-60 ◽  
Author(s):  
Alexandre Coutté ◽  
Gérard Olivier ◽  
Sylvane Faure
Keyword(s):  
Visual Search ◽  
Visual Target ◽  
Motor Planning ◽  
Search Performance ◽  
Response Preparation ◽  
Manual Response ◽  
Response Hand ◽  
Computer Screen ◽  
Left Hand ◽  
Manual Interaction

Computer use generally requires manual interaction with human-computer interfaces. In this experiment, we studied the influence of manual response preparation on co-occurring shifts of attention to information on a computer screen. The participants were to carry out a visual search task on a computer screen while simultaneously preparing to reach for either a proximal or distal switch on a horizontal device, with either their right or left hand. The response properties were not predictive of the target’s spatial position. The results mainly showed that the preparation of a manual response influenced visual search: (1) The visual target whose location was congruent with the goal of the prepared response was found faster; (2) the visual target whose location was congruent with the laterality of the response hand was found faster; (3) these effects have a cumulative influence on visual search performance; (4) the magnitude of the influence of the response goal on visual search is marginally negatively correlated with the rapidity of response execution. These results are discussed in the general framework of structural coupling between perception and motor planning.

Smart teaching mode based on particle swarm image recognition and human-computer interaction deep learning

2020 ◽  
Vol 39 (4) ◽  
pp. 5699-5711
Author(s):  
Shirong Long ◽  
Xuekong Zhao
Keyword(s):  
Feature Extraction ◽  
Particle Swarm Optimization ◽  
Deep Learning ◽  
Real Time ◽  
Image Recognition ◽  
Particle Swarm ◽  
Learning Technology ◽  
Search Performance ◽  
Swarm Optimization ◽  
Teaching Mode

The smart teaching mode overcomes the shortcomings of traditional teaching online and offline, but there are certain deficiencies in the real-time feature extraction of teachers and students. In view of this, this study uses the particle swarm image recognition and deep learning technology to process the intelligent classroom video teaching image and extracts the classroom task features in real time and sends them to the teacher. In order to overcome the shortcomings of the premature convergence of the standard particle swarm optimization algorithm, an improved strategy for multiple particle swarm optimization algorithms is proposed. In order to improve the premature problem in the search performance algorithm of PSO algorithm, this paper combines the algorithm with the useful attributes of other algorithms to improve the particle diversity in the algorithm, enhance the global search ability of the particle, and achieve effective feature extraction. The research indicates that the method proposed in this paper has certain practical effects and can provide theoretical reference for subsequent related research.

Center of Mass Theorem and the Separation of Variables for Two-Body System on a Three-Dimensional Sphere

2020 ◽  
Vol 23 (3) ◽  
pp. 306-311
Author(s):  
Yu. Kurochkin ◽  
Dz. Shoukavy ◽  
I. Boyarina
Keyword(s):  
Constant Curvature ◽  
Jacobi Equation ◽  
Separation Of Variables ◽  
Center Of Mass ◽  
Three Dimensional ◽  
Relative Distance ◽  
Dimensional Sphere ◽  
Body System ◽  
Spaces Of Constant Curvature ◽  
Hamilton Jacobi Equation

The immobility of the center of mass in spaces of constant curvature is postulated based on its definition obtained in [1]. The system of two particles which interact through a potential depending only on the distance between particles on a three-dimensional sphere is considered. The Hamilton-Jacobi equation is formulated and its solutions and trajectory equations are found. It was established that the reduced mass of the system depends on the relative distance.

Sign in / Sign up

Export Citation Format

Share Document