scholarly journals Stereo Slant Discrimination of Planar 3D Surfaces: Standard vs. Planar Cross-Correlation

2021 ◽  
Author(s):  
Can Oluk ◽  
Kathryn Bonnen ◽  
Johannes Burge ◽  
Lawrence K. Cormack ◽  
Wilson S. Geisler
Keyword(s):  
Human Performance ◽  
Cross Correlation ◽  
Discrimination Performance ◽  
Ideal Observer ◽  
The Other ◽  
Test Surface ◽  
Textured Surfaces ◽  
Ideal Observers ◽  
Binocular Stereo ◽  
Model Observers

AbstractBinocular stereo cues are important for discriminating 3D surface orientation, especially at near distances. We devised a single-interval task where observers discriminated the slant of a densely textured planar test surface relative to a textured planar surround reference surface. Although surfaces were rendered with correct perspective, the stimuli were designed so that the binocular cues dominated performance. Slant discrimination performance was measured as a function of the reference slant and the level of uncorrelated white noise added to the test-plane images in the left and right eye. We compared human performance with an approximate ideal observer (planar cross correlation, PCC) and two sub-ideal observers. The PCC observer uses the image in one eye and back projection to predict the test image in the other eye for all possible slants, tilts, and distances. The estimated slant, tilt, and distance are determined by the prediction that most closely matches the measured image in the other eye. The first sub-ideal observer (local PCC, LPCC) applies planar cross correlation over local neighborhoods and then pools estimates across the test plane. The second sub-optimal observer (standard cross correlation, SCC), uses only positional disparity information. We find that the ideal observer (PCC) and the first sub-ideal observer (LPCC) outperform the second sub-ideal observer (SCC), demonstrating the benefits of structural disparities. We also find that all three model observers can account for human performance, if two free parameters are included: a fixed small level of internal estimation noise, and a fixed overall efficiency scalar on slant discriminability.PrecisWe measured human stereo slant discrimination thresholds for accurately-rendered textured surfaces designed so that performance is dominated by binocular-disparity cues. We compared human performance with an approximate ideal observer and two sub-ideal observers.

scholarly journals Do people ask good questions?

2018 ◽  
Author(s):  
Anselm Rothe ◽  
Brenden M. Lake ◽  
Todd Matthew Gureckis
Keyword(s):  
Natural Language ◽  
Ideal Observer ◽  
The Other ◽  
Free Form ◽  
Question Generation ◽  
Limited Ability ◽  
Ideal Observers ◽  
The World ◽  
Ideal Observer Analysis ◽  
The One

People ask questions in order to efficiently learn about the world. But do people ask good questions? In this work, we designed an intuitive, game-based task that allowed people to ask natural language questions to resolve their uncertainty. Question quality was measured through Bayesian ideal-observer models that considered large spaces of possible game states. During free-form question generation, participants asked a creative variety of useful and goal-directed questions, yet they rarely asked the best questions as identified by the Bayesian ideal-observers (Experiment 1). In subsequent experiments, participants strongly preferred the best questions when evaluating questions that they did not generate themselves (Experiments 2 & 3). On the one hand, our results show that people can accurately evaluate question quality, even when the set of questions is diverse and an ideal-observer analysis has large computational requirements. On the other hand, people have a limited ability to synthesize maximally-informative questions from scratch, suggesting a bottleneck in the question asking process.

Correlational Methods for Analysis of Dance Movements

2011 ◽  
Vol 29 (supplement) ◽  
pp. 283-304 ◽  
Author(s):  
Timothy R. Brick ◽  
Steven M. Boker
Keyword(s):  
Motion Capture ◽  
Mirror Symmetry ◽  
Cross Correlation ◽  
The Other ◽  
Free Form ◽  
Motion Capture Data ◽  
Complex Interactions ◽  
Dance Movements ◽  
Time Lagged ◽  
Insight Into

Among the qualities that distinguish dance from other types of human behavior and interaction are the creation and breaking of synchrony and symmetry. The combination of symmetry and synchrony can provide complex interactions. For example, two dancers might make very different movements, slowing each time the other sped up: a mirror symmetry of velocity. Examining patterns of synchrony and symmetry can provide insight into both the artistic nature of the dance, and the nature of the perceptions and responses of the dancers. However, such complex symmetries are often difficult to quantify. This paper presents three methods – Generalized Local Linear Approximation, Time-lagged Autocorrelation, and Windowed Cross-correlation – for the exploration of symmetry and synchrony in motion-capture data as is it applied to dance and illustrate these with examples from a study of free-form dance. Combined, these techniques provide powerful tools for the examination of the structure of symmetry and synchrony in dance.

scholarly journals Bayesian natural selection and the evolution of perceptual systems

2002 ◽  
Vol 357 (1420) ◽  
pp. 419-448 ◽  
Author(s):  
Wilson S. Geisler ◽  
Randy L. Diehl
Keyword(s):  
Natural Selection ◽  
Decision Theory ◽  
Ideal Observer ◽  
Statistical Decision Theory ◽  
Statistical Decision ◽  
Natural Stimuli ◽  
Ideal Observers ◽  
Formal Framework ◽  
Bayesian Statistical Decision Theory ◽  
Perceptual Systems

In recent years, there has been much interest in characterizing statistical properties of natural stimuli in order to better understand the design of perceptual systems. A fruitful approach has been to compare the processing of natural stimuli in real perceptual systems with that of ideal observers derived within the framework of Bayesian statistical decision theory. While this form of optimization theory has provided a deeper understanding of the information contained in natural stimuli as well as of the computational principles employed in perceptual systems, it does not directly consider the process of natural selection, which is ultimately responsible for design. Here we propose a formal framework for analysing how the statistics of natural stimuli and the process of natural selection interact to determine the design of perceptual systems. The framework consists of two complementary components. The first is a maximum fitness ideal observer, a standard Bayesian ideal observer with a utility function appropriate for natural selection. The second component is a formal version of natural selection based upon Bayesian statistical decision theory. Maximum fitness ideal observers and Bayesian natural selection are demonstrated in several examples. We suggest that the Bayesian approach is appropriate not only for the study of perceptual systems but also for the study of many other systems in biology.

scholarly journals Tactile orientation perception: an ideal observer analysis of human psychophysical performance in relation to macaque area 3b receptive fields

2015 ◽  
Vol 114 (6) ◽  
pp. 3076-3096 ◽  
Author(s):  
Ryan M. Peters ◽  
Phillip Staibano ◽  
Daniel Goldreich
Keyword(s):  
Cortical Neurons ◽  
Human Performance ◽  
Spatial Perception ◽  
Receptive Fields ◽  
Human Perception ◽  
Ideal Observer ◽  
Orientation Discrimination ◽  
Orientation Perception ◽  
Area 3B ◽  
The Ideal

The ability to resolve the orientation of edges is crucial to daily tactile and sensorimotor function, yet the means by which edge perception occurs is not well understood. Primate cortical area 3b neurons have diverse receptive field (RF) spatial structures that may participate in edge orientation perception. We evaluated five candidate RF models for macaque area 3b neurons, previously recorded while an oriented bar contacted the monkey's fingertip. We used a Bayesian classifier to assign each neuron a best-fit RF structure. We generated predictions for human performance by implementing an ideal observer that optimally decoded stimulus-evoked spike counts in the model neurons. The ideal observer predicted a saturating reduction in bar orientation discrimination threshold with increasing bar length. We tested 24 humans on an automated, precision-controlled bar orientation discrimination task and observed performance consistent with that predicted. We next queried the ideal observer to discover the RF structure and number of cortical neurons that best matched each participant's performance. Human perception was matched with a median of 24 model neurons firing throughout a 1-s period. The 10 lowest-performing participants were fit with RFs lacking inhibitory sidebands, whereas 12 of the 14 higher-performing participants were fit with RFs containing inhibitory sidebands. Participants whose discrimination improved as bar length increased to 10 mm were fit with longer RFs; those who performed well on the 2-mm bar, with narrower RFs. These results suggest plausible RF features and computational strategies underlying tactile spatial perception and may have implications for perceptual learning.

Time-Based Modeling of Human Performance

2005 ◽  
Vol 49 (12) ◽  
pp. 1200-1204 ◽  
Author(s):  
Esa M. Rantanen ◽  
Brian R. Levinthal
Keyword(s):  
Human Performance ◽  
Mental Workload ◽  
Probabilistic Approach ◽  
The Other ◽  
Performance Variables ◽  
The Mean ◽  
And Performance ◽  
Methods Of Measurement

This paper presents a probabilistic approach to modeling human performance. Instead of focusing on mean performance, the effects of taskload on the distributions of performance variables are examined. From such data, probabilities of given levels of performance can be derived and methods of measurement that expand the analyses beyond those of the mean developed. Results from two experiments, one abstract, the other realistic, are presented in terms of timely performance on required tasks. As taskload increased, the participants were less likely to act on the experimental tasks at an earliest opportunity than under low taskload, resulting in increase of “too late” errors. Measurement of taskload and performance in temporal terms also allowed for bracketing and making inferences about mental workload, which is not directly measurable.

Dynamic Behavior and Synchronization of an Automobile as a Complex System

2014 ◽  
Author(s):  
Claudia A. González-Cruz ◽  
Juan C. Jáuregui-Correa ◽  
Carlos S. López-Cajún ◽  
Mihir Sen
Keyword(s):  
Complex System ◽  
Wavelet Transforms ◽  
Cross Correlation ◽  
Correlation Coefficients ◽  
The Other ◽  
Accelerometer Data ◽  
Hilbert Transforms ◽  
The Road ◽  
The Individual ◽  
Analytical Tools

A complex system is composed of many interacting components, but the behavior of the system as a whole can be quite different from that of the individual components. An automobile is an example of a common mechanical system composed of a large number of individual components that are mechanically connected in some way and hence transmit vibrations to each other. This paper proposes a variety of inter-related analytical tools for the study of experimental data from such systems. In this work, experimental results of accelerometer data acquired at two locations in the automobile for two different kinds of tests are analyzed. One test is the response to impact on a stationary vehicle, and the other is the road-response to the vehicle being driven on a flat road at different speeds. Signals were processed via Fourier and wavelet transforms, cross-correlation coefficients were computed, and Hilbert transforms and Kuramoto order parameters were determined. A new parameter representing synchronization deficit is introduced. There is indeed some degree of synchronization that can be quantified between the accelerations measured at these two locations in the vehicle.

Perceptual Classification Images from Vernier Acuity Masked by Noise

Perception ◽  
1996 ◽  
Vol 25 (1_suppl) ◽  
pp. 2-2 ◽  
Author(s):  
A J Ahumada
Keyword(s):  
Fourier Transforms ◽  
Internal Noise ◽  
Discrimination Performance ◽  
Ideal Observer ◽  
Classification Rule ◽  
Horizontal Line ◽  
Vernier Acuity ◽  
Perceptual Classification ◽  
Classification Images ◽  
The Ideal

Letting external noise rather than internal noise limit discrimination performance allows information to be extracted about the observer's stimulus classification rule. A perceptual classification image is the correlation over trials between the noise amplitude at a spatial location and the observer's responses. If, for example, the observer followed the rule of the ideal observer, the response correlation image would be an estimate of the ideal observer filter, the difference between the two unmasked images being discriminated. Perceptual classification images were estimated for a Vernier discrimination task. The display screen had 48 pixels deg−1 horizontally and vertically. The no-offset image had a dark horizontal line of 4 pixels, a 1 pixel space, and 4 more dark pixels. Classification images were based on 1600 discrimination trials with the line contrast adjusted to keep the error rate near 25%. In the offset image, the second line was one pixel higher. Unlike the ideal observer filter (a horizontal dipole), the observer perceptual classification images are strongly oriented. Fourier transforms of the classification images had a peak amplitude near 1 cycle deg−1 and an orientation near 25 deg. The spatial spread is much more than image blur predicts, and probably indicates the spatial position uncertainty in the task.

scholarly journals Reliability Evaluation of the Data Acquisition Potential of a Low-Cost Climatic Network for Applications in Agriculture

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6597
Author(s):  
Sergio Trilles ◽  
Pablo Juan ◽  
Carlos Díaz-Avalos ◽  
Sara Ribeiro ◽  
Marco Painho
Keyword(s):  
Data Acquisition ◽  
Strong Influence ◽  
Cross Correlation ◽  
Low Cost ◽  
Central Zone ◽  
Climatic Conditions ◽  
The Other ◽  
Sensor Nodes ◽  
Disease Models ◽  
Similarity Analysis

Temperature, humidity and precipitation have a strong influence on the generation of diseases in different crops, especially in vine. In recent years, advances in different disciplines have enabled the deployment of sensor nodes on agricultural plots. These sensors are characterised by a low cost and so the reliability of the data obtained from them can be compromised, as they are built from low-confidence components. In this research, two studies were carried out to determine the reliability of the data obtained by different SEnviro nodes installed in vineyards. Two networks of meteorological stations were used to carry out these studies, one official and the other professional. The first study was based on calculating the homogenisation of the data, which was performed using the Climatol tool. The second study proposed a similarity analysis using cross-correlation. The results showed that the low-cost node can be used to monitor climatic conditions in an agricultural area in the central zone of the province of Castelló (Spain) and to obtain reliable observations for use in previously published fungal disease models.

Properties of random functions

1956 ◽  
Vol 52 (4) ◽  
pp. 672-686 ◽  
Author(s):  
D. S. Palmer
Keyword(s):  
Cross Correlation ◽  
The Other ◽  
Horizontal Line ◽  
Time Lags ◽  
Frequency Distributions ◽  
Random Functions ◽  
Wave Radio ◽  
Long Wave ◽  
Radio Signals ◽  
Highly Correlated

ABSTRACTThis paper deals with the relationships of the maxima, minima and zeros of two random functions of known autocorrelations and cross-correlation, based on the work of Rice(4). Ratcliffe(3) and Briggs and Spencer(2) discuss a similar problem in connexion with a ‘Phillips Record’ of an experiment in ionospheric reflexion. In this experiment there are two highly correlated reflected signals, their maxima coming close together, and the record shows the time lags between a maximum on one signal and a maximum on the other. Briggs and Page (1) have made an experimental study of the distribution of the differences between the positions of the maxima of two highly correlated random functions, using EDSAC to construct the functions. In §§ 3–7 the frequency distributions of intervals between successive zeros and maxima, and of the lengths of intercepts by a horizontal line, are considered. This has applications to the study of the fading of long-wave radio signals, where the tune differences between successive maxima of the amplitude have been investigated.

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