|
|
Analysis of the robustness of the psychometric functions
Myšička, Pavel ; Děchtěrenko, Filip (advisor) ; Pilát, Martin (referee)
Psychophysics offers a wide range of experimental techniques to study human percep- tion and often uses mathematical models to do so. Psychometrical function is a formal model of the relationship between intensity of stimulus and perception, that is used by psychophysics to model experimental data. There are various types of psychometric functions used in psychophysical practice. So far it is unknown whether use of different psychometric functions in model experiment data can influence the results of experiment. The goal of this work is to explore differences between commonly used psychometric func- tions, prove if there are any differences between their ability to estimate psychometric data and if these differences are big enough so that researchers should pay attention to choice of psychometric function. 1
|
|
|
Perceptual learning and Ideal Bayesian obsever in visual search task
Němeček, Viktor ; Děchtěrenko, Filip (advisor) ; Pilát, Martin (referee)
Searching for objects in a complex environment is an activity we do many times each day. Najemnik and Geisler (2005; 2008; 2009) showed in their work that people do not perform optimally, and devised multiple ideal observer models for one particular visual search task. In this thesis we tried to show that if people get feedback from one of the ideal observer models, they learn to solve the task better during a given amount of trials than they would without the feedback. We were unable to prove any nontrivial result with statistical significance due to a small sample size, but the data suggests that the feedback indeed has a positive effect on the learning, and that the continuation of the research is justified. An iOS application necessary for the experiment was created as a part of the thesis. Aside from the experiment itself, one can also use it to play a visual search testing game. 1
|
|
|
Relationships among characteristics perceived from photos of faces
Machová, Kamila ; Flegr, Jaroslav (advisor) ; Děchtěrenko, Filip (referee)
Estimating others characteristics from facial cues plays an important role in our everyday lives. People usually agree in these estimates well and many of these estimates correlate. Majority studies consider one or few character- istics only and their respondents usually are in narrow ranges of ages. This study is partly based on rating of 13 characteristics of 80 men's and women's faces by respondents of various ages. These data were originally collected within yet unpublished study of Jaroslav Flegr, Amy E. Blum and Šebastian Kroupa. In this study I most strikingly found out that: i) older respondents of both genders rates photos of women as more attractive, ii) respondents spend more time by rating faces considered by themselves as more attractive or nice, iii) men rate people with different eye color as more attractive and women rate others with the same eye color as nicer, iv) preferences computed by two methods do not differ much. 1
|
|
|
Comparison of scan patterns in dynamic tasks
Děchtěrenko, Filip ; Lukavský, Jiří (advisor) ; Nyström, Marcus (referee) ; Paluš, Milan (referee)
Eye tracking is commonly used in many scientific fields (experimental psychology, neuroscience, behavioral economics, etc.) and can provide us with rigorous data about current allocation of attention. Due to the complexity of data processing and missing methodology, experimental designs are often limited to static stimuli; eye tracking data is analyzed only with respect to basic types of eye movements - fixation and saccades. In dynamic tasks (e.g. with dynamic stimuli, such as showing movies or Multiple Object Tracking task), another type of eye movement is commonly present: smooth pursuit. Importantly, eye tracking data from dynamic tasks is often represented as raw data samples. It requires a different approach to analyze the data, and there are a lot of methodological gaps in analytical tools. This thesis is divided into three parts. In the first part, we gave an overview of current methods for analyzing scan patterns, followed by four simulations, in which we systematically distort scan patterns and measure the similarity using several commonly used metrics. In the second part, we presented the current approaches to statistical testing of differences between groups of scan patterns. We present two novel strategies for analyzing statistically significant differences between groups of scan patterns and...
|
|
|
Comparison of signatures using metrics for the eye movements
Vyhlas, Petr ; Děchtěrenko, Filip (advisor) ; Gemrot, Jakub (referee)
Comparison of signatures is part of the identity verification. The study focuses on comparison of signatures using metrics for the eye movements. In first part of study we review algorithms for the signature verification and we introduce metrics for comparing eye movements. We used Levenshtein distance, Fréchet distance and correlation coefficient for the comparison of signatures. We discovered behavior of these metrics and choose their combination for the computation of percentage similarity between two signatures. We designed and implemented universal Windows application which digitizes signatures, compares two signatures and determines their similarity. We conducted an experiment in which participants tried to sign themselves or tried to sign someone else. We did not find improvement during the signing. Powered by TCPDF (www.tcpdf.org)
|
|
|
Predicting targets in Multiple Object Tracking task
Citorík, Juraj ; Děchtěrenko, Filip (advisor) ; Brunetto, Robert (referee)
The aim of this thesis is to predict targets in a Multiple Object Tracking (MOT) task, in which subjects track multiple moving objects. We processed and analyzed data containing object and gaze position information from 1148 MOT trials completed by 20 subjects. We extracted multiple features from the raw data and designed a machine learning approach for the prediction of targets using neural networks and hidden Markov models. We assessed the performance of the models and features. The results of our experiments show that it is possible to train a machine learning model to predict targets with very high accuracy. 1
|
|
|
Ideal Bayesian Observer with reduced detectability map
Amemori, Josef ; Děchtěrenko, Filip (advisor) ; Brom, Cyril (referee)
Title: Ideal Bayesian Observer with reduced detectability map Author: Josef Amemori Department: Department of Software and Computer Science Education Supervisor: Mgr. Filip Děchtěrenko, Department of Software and Computer Science Education Abstract: A computational modeling of the human vision is a challenging task. In recent years, a biologically inspired model Ideal Bayesian Observer was created for the visual search task (Najemnik & Geisler, 2005). The model predicts eye movements when searching for Gabor patch in 1/f noise. In their work, they observed similarity between distributions of fixations and saccades predicted by Ideal Bayesian Observer and distributions of fixations and saccades from a human observer. In this work, we have implemented Ideal Bayesian Observer with degenerated visual field and compared the model with behavior of a human. Keywords: Ideal Bayesian Observer, eye movements, modeling, central scotoma
|
|
|
Space shooter game with mutually cooperating bots
Hýbl, Oskar ; Zavoral, Filip (advisor) ; Děchtěrenko, Filip (referee)
The goal of this thesis is to, based on several AI algorithms, design and implement an AI for a game called Space Shooter which was developed as an Academic Year Project. In this game there are two groups of spaceships fighting against each other with the player directly controlling one of the ships. The created AI module is supposed to ensure the cooperation of the agents controlling the ships. The resulting program has an emphasis on modularity and extensibility, so that, in case of further development of Space Shooter, modification of the AI would be facilitated as much as possible. Powered by TCPDF (www.tcpdf.org)
|
|
|
Multi-agent pathfinding with air transports
Kozma, Matouš ; Černý, Martin (advisor) ; Děchtěrenko, Filip (referee)
In most real-time strategy (RTS) games the problem of finding the shortest path for multiple units in real-time has to be solved many times during one match. That problem is known to be difficult, but some games require solving an even more complicated version of the problem where, in addition to land-based units, there are aerial transports, which are able to move everywhere around the map and to load a unit at one place and unload it somewhere else. In this thesis we introduce a new family of algorithms based on a greedy algorithm, which also serves as a basis for the primitive solutions used in games today. We implement these algorithms in the RTS game Starcraft and evaluate their effectiveness. From these tests we choose the one with the best performance as the solution of this thesis.
|
|
|
Analysis of multidimensional contingency tables
Děchtěrenko, Filip ; Boschek, Petr (advisor) ; Vranka, Marek (referee)
Multidimensional contingency tables are suitable tool for capturing the count of observations of multiple categorical variables. There are more complex relationships amongst multiple variables which cannot be captured by analytical tools for two variables. In this work, we introduced log-linear models and showed their application on three dimensional tables. We focused on statistical program SPSS, in which we showed analysis on the sample data including the interpretation. We redone the analysis on another artificial data capturing the possible situations which could researcher encounter in the real life. The sample data were also analyzed in statistical program R. Powered by TCPDF (www.tcpdf.org)
|
guest ::
RSS feed.