@phdthesis{Rothkegel2018, author = {Rothkegel, Lars Oliver Martin}, title = {Human scanpaths in natural scene viewing and natural scene search}, doi = {10.25932/publishup-42000}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-420005}, school = {Universit{\"a}t Potsdam}, pages = {xv, 131}, year = {2018}, abstract = {Understanding how humans move their eyes is an important part for understanding the functioning of the visual system. Analyzing eye movements from observations of natural scenes on a computer screen is a step to understand human visual behavior in the real world. When analyzing eye-movement data from scene-viewing experiments, the impor- tant questions are where (fixation locations), how long (fixation durations) and when (ordering of fixations) participants fixate on an image. By answering these questions, computational models can be developed which predict human scanpaths. Models serve as a tool to understand the underlying cognitive processes while observing an image, especially the allocation of visual attention. The goal of this thesis is to provide new contributions to characterize and model human scanpaths on natural scenes. The results from this thesis will help to understand and describe certain systematic eye-movement tendencies, which are mostly independent of the image. One eye-movement tendency I focus on throughout this thesis is the tendency to fixate more in the center of an image than on the outer parts, called the central fixation bias. Another tendency, which I will investigate thoroughly, is the characteristic distribution of angles between successive eye movements. The results serve to evaluate and improve a previously published model of scanpath generation from our laboratory, the SceneWalk model. Overall, six experiments were conducted for this thesis which led to the following five core results: i) A spatial inhibition of return can be found in scene-viewing data. This means that locations which have already been fixated are afterwards avoided for a certain time interval (Chapter 2). ii) The initial fixation position when observing an image has a long-lasting influence of up to five seconds on further scanpath progression (Chapter 2 \& 3). iii) The often described central fixation bias on images depends strongly on the duration of the initial fixation. Long-lasting initial fixations lead to a weaker central fixation bias than short fixations (Chapter 2 \& 3). iv) Human observers adjust their basic eye-movement parameters, like fixation dura- tions and saccade amplitudes, to the visual properties of a target they look for in visual search (Chapter 4). v) The angle between two adjacent saccades is an indicator for the selectivity of the upcoming saccade target (Chapter 4). All results emphasize the importance of systematic behavioral eye-movement tenden- cies and dynamic aspects of human scanpaths in scene viewing.}, language = {en} } @phdthesis{AbdelwahabHusseinAbdelwahabElsayed2019, author = {Abdelwahab Hussein Abdelwahab Elsayed, Ahmed}, title = {Probabilistic, deep, and metric learning for biometric identification from eye movements}, doi = {10.25932/publishup-46798}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-467980}, school = {Universit{\"a}t Potsdam}, pages = {vi, 65}, year = {2019}, abstract = {A central insight from psychological studies on human eye movements is that eye movement patterns are highly individually characteristic. They can, therefore, be used as a biometric feature, that is, subjects can be identified based on their eye movements. This thesis introduces new machine learning methods to identify subjects based on their eye movements while viewing arbitrary content. The thesis focuses on probabilistic modeling of the problem, which has yielded the best results in the most recent literature. The thesis studies the problem in three phases by proposing a purely probabilistic, probabilistic deep learning, and probabilistic deep metric learning approach. In the first phase, the thesis studies models that rely on psychological concepts about eye movements. Recent literature illustrates that individual-specific distributions of gaze patterns can be used to accurately identify individuals. In these studies, models were based on a simple parametric family of distributions. Such simple parametric models can be robustly estimated from sparse data, but have limited flexibility to capture the differences between individuals. Therefore, this thesis proposes a semiparametric model of gaze patterns that is flexible yet robust for individual identification. These patterns can be understood as domain knowledge derived from psychological literature. Fixations and saccades are examples of simple gaze patterns. The proposed semiparametric densities are drawn under a Gaussian process prior centered at a simple parametric distribution. Thus, the model will stay close to the parametric class of densities if little data is available, but it can also deviate from this class if enough data is available, increasing the flexibility of the model. The proposed method is evaluated on a large-scale dataset, showing significant improvements over the state-of-the-art. Later, the thesis replaces the model based on gaze patterns derived from psychological concepts with a deep neural network that can learn more informative and complex patterns from raw eye movement data. As previous work has shown that the distribution of these patterns across a sequence is informative, a novel statistical aggregation layer called the quantile layer is introduced. It explicitly fits the distribution of deep patterns learned directly from the raw eye movement data. The proposed deep learning approach is end-to-end learnable, such that the deep model learns to extract informative, short local patterns while the quantile layer learns to approximate the distributions of these patterns. Quantile layers are a generic approach that can converge to standard pooling layers or have a more detailed description of the features being pooled, depending on the problem. The proposed model is evaluated in a large-scale study using the eye movements of subjects viewing arbitrary visual input. The model improves upon the standard pooling layers and other statistical aggregation layers proposed in the literature. It also improves upon the state-of-the-art eye movement biometrics by a wide margin. Finally, for the model to identify any subject — not just the set of subjects it is trained on — a metric learning approach is developed. Metric learning learns a distance function over instances. The metric learning model maps the instances into a metric space, where sequences of the same individual are close, and sequences of different individuals are further apart. This thesis introduces a deep metric learning approach with distributional embeddings. The approach represents sequences as a set of continuous distributions in a metric space; to achieve this, a new loss function based on Wasserstein distances is introduced. The proposed method is evaluated on multiple domains besides eye movement biometrics. This approach outperforms the state of the art in deep metric learning in several domains while also outperforming the state of the art in eye movement biometrics.}, language = {en} } @phdthesis{Ohl2013, author = {Ohl, Sven}, title = {Small eye movements during fixation : the case of postsaccadic fixation and preparatory influences}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-69862}, school = {Universit{\"a}t Potsdam}, year = {2013}, abstract = {Describing human eye movement behavior as an alternating sequence of saccades and fixations turns out to be an oversimplification because the eyes continue to move during fixation. Small-amplitude saccades (e.g., microsaccades) are typically observed 1-2 times per second during fixation. Research on microsaccades came in two waves. Early studies on microsaccades were dominated by the question whether microsaccades affect visual perception, and by studies on the role of microsaccades in the process of fixation control. The lack of evidence for a unique role of microsaccades led to a very critical view on the importance of microsaccades. Over the last years, microsaccades moved into focus again, revealing many interactions with perception, oculomotor control and cognition, as well as intriguing new insights into the neurophysiological implementation of microsaccades. In contrast to early studies on microsaccades, recent findings on microsaccades were accompanied by the development of models of microsaccade generation. While the exact generating mechanisms vary between the models, they still share the assumption that microsaccades are generated in a topographically organized saccade motor map that includes a representation for small-amplitude saccades in the center of the map (with its neurophysiological implementation in the rostral pole of the superior colliculus). In the present thesis I criticize that models of microsaccade generation are exclusively based on results obtained during prolonged presaccadic fixation. I argue that microsaccades should also be studied in a more natural situation, namely the fixation following large saccadic eye movements. Studying postsaccadic fixation offers a new window to falsify models that aim to account for the generation of small eye movements. I demonstrate that error signals (visual and extra-retinal), as well as non-error signals like target eccentricity influence the characteristics of small-amplitude eye movements. These findings require a modification of a model introduced by Rolfs, Kliegl and Engbert (2008) in order to account for the generation of small-amplitude saccades during postsaccadic fixation. Moreover, I present a promising type of survival analysis that allowed me to examine time-dependent influences on postsaccadic eye movements. In addition, I examined the interplay of postsaccadic eye movements and postsaccadic location judgments, highlighting the need to include postsaccadic eye movements as covariate in the analyses of location judgments in the presented paradigm. In a second goal, I tested model predictions concerning preparatory influences on microsaccade generation during presaccadic fixation. The observation, that the preparatory set significantly influenced microsaccade rate, supports the critical model assumption that increased fixation-related activity results in a larger number of microsaccades. In the present thesis I present important influences on the generation of small-amplitude saccades during fixation. These eye movements constitute a rich oculomotor behavior which still poses many research questions. Certainly, small-amplitude saccades represent an interesting source of information and will continue to influence future studies on perception and cognition.}, language = {en} } @phdthesis{Mergenthaler2009, author = {Mergenthaler, Konstantin K.}, title = {The control of fixational eye movements}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-29397}, school = {Universit{\"a}t Potsdam}, year = {2009}, abstract = {In normal everyday viewing, we perform large eye movements (saccades) and miniature or fixational eye movements. Most of our visual perception occurs while we are fixating. However, our eyes are perpetually in motion. Properties of these fixational eye movements, which are partly controlled by the brainstem, change depending on the task and the visual conditions. Currently, fixational eye movements are poorly understood because they serve the two contradictory functions of gaze stabilization and counteraction of retinal fatigue. In this dissertation, we investigate the spatial and temporal properties of time series of eye position acquired from participants staring at a tiny fixation dot or at a completely dark screen (with the instruction to fixate a remembered stimulus); these time series were acquired with high spatial and temporal resolution. First, we suggest an advanced algorithm to separate the slow phases (named drift) and fast phases (named microsaccades) of these movements, which are considered to play different roles in perception. On the basis of this identification, we investigate and compare the temporal scaling properties of the complete time series and those time series where the microsaccades are removed. For the time series obtained during fixations on a stimulus, we were able to show that they deviate from Brownian motion. On short time scales, eye movements are governed by persistent behavior and on a longer time scales, by anti-persistent behavior. The crossover point between these two regimes remains unchanged by the removal of microsaccades but is different in the horizontal and the vertical components of the eyes. Other analyses target the properties of the microsaccades, e.g., the rate and amplitude distributions, and we investigate, whether microsaccades are triggered dynamically, as a result of earlier events in the drift, or completely randomly. The results obtained from using a simple box-count measure contradict the hypothesis of a purely random generation of microsaccades (Poisson process). Second, we set up a model for the slow part of the fixational eye movements. The model is based on a delayed random walk approach within the velocity related equation, which allows us to use the data to determine control loop durations; these durations appear to be different for the vertical and horizontal components of the eye movements. The model is also motivated by the known physiological representation of saccade generation; the difference between horizontal and vertical components concurs with the spatially separated representation of saccade generating regions. Furthermore, the control loop durations in the model suggest an external feedback loop for the horizontal but not for the vertical component, which is consistent with the fact that an internal feedback loop in the neurophysiology has only been identified for the vertical component. Finally, we confirmed the scaling properties of the model by semi-analytical calculations. In conclusion, we were able to identify several properties of the different parts of fixational eye movements and propose a model approach that is in accordance with the described neurophysiology and described limitations of fixational eye movement control.}, language = {en} }