Nothing more than a pair of curvatures: A common mechanism for the detection of both radial and non-radial frequency patterns.
نویسندگان
چکیده
Radial frequency (RF) patterns, which are sinusoidal modulations of a radius in polar coordinates, are commonly used to study shape perception. Previous studies have argued that the detection of RF patterns is either achieved globally by a specialized global shape mechanism, or locally using as cue the maximum tangent orientation difference between the RF pattern and the circle. Here we challenge both ideas and suggest instead a model that accounts not only for the detection of RF patterns but also for line frequency patterns (LF), i.e. contours sinusoidally modulated around a straight line. The model has two features. The first is that the detection of both RF and LF patterns is based on curvature differences along the contour. The second is that this curvature metric is subject to what we term the Curve Frequency Sensitivity Function, or CFSF, which is characterized by a flat followed by declining response to curvature as a function of modulation frequency, analogous to the modulation transfer function of the eye. The evidence that curvature forms the basis for detection is that at very low modulation frequencies (1-3 cycles for the RF pattern) there is a dramatic difference in thresholds between the RF and LF patterns, a difference however that disappears at medium and high modulation frequencies. The CFSF feature on the other hand explains why thresholds, rather than continuously declining with modulation frequency, asymptote at medium and high modulation frequencies. In summary, our analysis suggests that the detection of shape modulations is processed by a common curvature-sensitive mechanism that is subject to a shape-frequency-dependent transfer function. This mechanism is independent of whether the modulation is applied to a circle or a straight line.
منابع مشابه
Radial Basis Neural Network Based Islanding Detection in Distributed Generation
This article presents a Radial Basis Neural Network (RBNN) based islanding detection technique. Islanding detection and prevention is a mandatory requirement for grid-connected distributed generation (DG) systems. Several methods based on passive and active detection scheme have been proposed. While passive schemes have a large non detection zone (NDZ), concern has been raised on active method ...
متن کاملExact Radial Free Vibration Frequencies of Power-Law Graded Spheres
This study concentrates on the free pure radial vibrations of hollow spheres made of hypothetically functionally simple power rule graded materials having identical inhomogeneity indexes for both Young’s modulus and the density in an analytical manner. After offering the exact elements of the free vibration coefficient matrices for free-free, free-fixed, and fixed-fixed restraints, a parametric...
متن کاملBedside Ultrasonography for Early Diagnosis of Occult Radial Head Fractures in Emergency Room: A CTComparative Diagnostic Study
Background: Some of the Mason type I fractures cannot be detected on early radiographic images. These occultfractures are considered as a diagnostic challenge for physicians. Our aim was to determine the value of bedsideultrasonography for the detection of Mason I radial head fractures that are non-visible in early X-ray’s.Methods: A prospective blind single-center diagnostic study was conducte...
متن کاملRadial Tunnel Syndrome, Diagnostic and Treatment Dilemma
Radial tunnel syndrome is a disease which we should consider it in elbow and forearm pains. It is diagnosed with lateral elbow and dorsal forearm pain may radiate to the wrist and dorsum of the fingers. The disease is more prevalent in women with the age of 30 to 50 years old. It occurs by intermittent compression on the radial nerve from the radial head to the inferior border of the supinator ...
متن کاملSome Conditions for Characterizing Minimum Face in Non-Radial DEA Models with Undesirable Outputs
The problem of utilizing undesirable (bad) outputs in DEA models often need replacing the assumption of free disposability of outputs by weak disposability of outputs. The Kuosmanen technology is the only correct representation of the fully convex technology exhibiting weak disposability of bad and good outputs. Also, there are some specific features of non-radial data envelopment analysis (DEA...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Vision research
دوره 134 شماره
صفحات -
تاریخ انتشار 2017