Task influence of scene content selected by active vision

This thesis investigated possible features that are used to guide saccadic eye movements in specific tasks, including a visual search task, answering questions about an image, and freely viewing images. Current eyetracking technology was used to gather eye movement records of subjects as they viewed images. A classical experiment that shows the influence of task on eye movements conducted by Alfred Yarbus was replicated under natural viewing conditions. In this experiment, 17 viewers were given a set of different instructions before viewing a Russian painting. Eye movement records were compared between tasks, and it was found that the instruction a viewer is given did affect which regions of the image are fixated. Even though the viewing times in the two experiments were drastically different (3 minutes compared to ~20 seconds), the behaviors of the 17 subjects were remarkably similar to the original record published by Yarbus; regions that were \u27informative\u27 for the task were fixated. Behavior between the 17 subjects (within one task) was more similar than between the seven tasks (within one subject). In a second experiment, 23 observers performed a visual search task in images of real-world scenes. Before each trial, the subject was shown a preview image of the target. This image was either pixel-for-pixel exactly as it appeared in the image (\u27Extracted Object\u27 condition) or was a cartoon icon representation of the target (\u27Cartoon Icon\u27 condition). On average, the reaction time in finding the target in the Cartoon Icon condition was 3.0 seconds, and less than 2.5 seconds in the Extracted Object condition. This increase in reaction time was caused primarily by the viewer taking longer to initially fixate on the target. Perceptual saliency and other feature content of the images at fixated and random locations were compared to gain insight into what features the visual system was using to guide, and expedite, visual search in each of the two conditions. Several commonly used metrics were used to measure the performance of each of 18 different topographical feature maps. It was found that feature maps that weight areas according to the color and spatial characteristics of the target perform better than general low-level saliency maps, showing that the visual system can be fine-tuned according to the task. However, a general model of visual attention for search in real-world scenes cannot be created using only low-level stimulus properties

Feeling full and being full : how gastric content relates to appetite, food properties and neural activation

Aim: This thesis aimed to further determine how gastric content relates to subjective experiences regarding appetite, how this relation is affected by food properties and whether this is visible in neural activation changes. Method: This was studied using questionnaires, MRI of the stomach and fMRI of the brain. Randomized, controlled crossover experiments with healthy men and for one experiment women were performed. Results: MRI measurements of the stomach as opposed to an indirect measurement by proxy, such as 13C breath testing are to be preferred. We show that gastric emptying is affected by energy load, and to a much smaller extent by viscosity. Additionally we show that a thick shake containing 100 kcal will yield higher fullness sensations than a thin shake containing 500 kcal. In the chapter we name this phenomenon ‘phantom fullness’, i.e., a sense of fullness and satiation caused by the taste and mouthfeel of a food which is irrespective of actual stomach fullness. A liquid meal followed by a drink of water empties about twice as fast in the first 35 minutes compared to the same amount of water incorporated within the liquid meal. Using MRI we were able to show layering within the stomach and increased emptying of this watery layer. With 300mL of increased gastric content inducing distention, appetite was lowered. Ingestion led to significant changes in activation in the right insula and parts of the left and right inferior frontal cortices over time. Women retain significantly more fluid after a carbonated drink in their stomach than men. When comparing correlations between subjective ratings and intragastric liquid and gas and total gastric volume, nausea and fullness correlated strongest with the liquid fraction within the stomach, bloating strongest with total gastric volume. Conclusion: There are marked differences betweengastric content and subjective experiences regarding appetite. Viscosity is a main driver of these differences. Combined gastric MRI and brain fMRI measurements need to be performed to understand this further.</p

Examining high level neural representations of cluttered scenes

Humans and other primates can rapidly categorize objects even when they are embedded in complex visual scenes (Thorpe et al., 1996; Fabre-Thorpe et al., 1998). Studies by Serre et al., 2007 have shown that the ability of humans to detect animals in brief presentations of natural images decreases as the size of the target animal decreases and the amount of clutter increases, and additionally, that a feedforward computational model of the ventral visual system, originally developed to account for physiological properties of neurons, shows a similar pattern of performance. Motivated by these studies, we recorded single- and multi-unit neural spiking activity from macaque superior temporal sulcus (STS) and anterior inferior temporal cortex (AIT), as a monkey passively viewed images of natural scenes. The stimuli consisted of 600 images of animals in natural scenes, and 600 images of natural scenes without animals in them, captured at four different viewing distances, and were the same images used by Serre et al. to allow for a direct comparison between human psychophysics, computational models, and neural data. To analyze the data, we applied population "readout" techniques (Hung et al., 2005; Meyers et al., 2008) to decode from the neural activity whether an image contained an animal or not. The decoding results showed a similar pattern of degraded decoding performance with increasing clutter as was seen in the human psychophysics and computational model results. However, overall the decoding accuracies from the neural data lower were than that seen in the computational model, and the latencies of information in IT were long (~125ms) relative to behavioral measures obtained from primates in other studies. Additional tests also showed that the responses of the model units were not capturing several properties of the neural responses, and that detecting animals in cluttered scenes using simple model units based on V1 cells worked almost as well as using more complex model units that were designed to model the responses of IT neurons. While these results suggest AIT might not be the primary brain region involved in this form of rapid categorization, additional studies are needed before drawing strong conclusions

A Dataset of Gaze Behavior in VR Faithful to Natural Statistics

Eye tracking technology is advancing swiftly and many areas of research have begun taking advantage of this. Existing eye trackers project gaze onto a 2D plane, whether it be the display of a head mounted virtual reality (VR) helmet or an image of a real life scene the user is in. This allows us to easily analyze what a viewer is looking at, but limits classification of gaze behaviors from this type of signal. Instead, a system that takes into account head movements within the same space as gaze velocity allows researchers to classify more advanced gaze behaviors such as smooth pursuits and fixations resulting from vestibulo-ocular reflex. For this work data is collected in real world environments where head and gaze movements are recorded over a variety of tasks. The resulting data is then used to construct a distribution of naturally occurring gaze behaviors. This distribution is then used to drive a VR data collection experiment that elicits specific gaze behaviors such as fixations and saccades with specific velocities and directions. A dataset of 12 subjects was collected while subjects play a shooting game in the virtual world. Data was analyzed to see if the intended eye movements were produced, and also to compare the eye movements that occur in fast versus slow presentation of targets

Seeing, sensing, and selection: modeling visual perception in complex environments

The purpose of this thesis is to investigate human visual perception at the level of eye movements by describing the interaction between vision and action during natural, everyday tasks in a real-world environment. The results of the investigation provide motivation for the development of a biologically-based model of selective visual perception that relies on the relative perceptual conspicuity of certain regions within the field of view. Several experiments were designed and conducted that form the basis for the model. The experiments provide evidence that the visual system is not passive, nor is it general-purpose, but rather it is active and specific, tightly coupled to the requirements of planned behavior and action. The implication for an active and task-specific visual system is that an explicit representation of the environment can be eschewed in favor of a compact representation with large potential savings in computational efficiency. The compact representation is in the form of a topographic map of relative perceptual conspicuity values. Other recent attempts at compact scene representations have focused mainly on low-level maps that code certain salient features of the scene including color, edges, and luminance. This study has found that the low-level maps do not correlate well with subjects\u27 fixation locations, therefore, a map of perceptual conspicuity is presented that incorporates high-level information. The high-level information is in the form of figure/ground segmentation, potential object detection, and task-specific location bias. The resulting model correlates well with the fixation densities of human viewers of natural scenes, and can be used as a pre-processing module for image understanding or intelligent surveillance applications

Eyetracking and Applied Linguistics

Eyetracking has become a powerful tool in scientific research and has finally found its way into disciplines such as applied linguistics and translation studies, paving the way for new insights and challenges in these fields. The aim of the first International Conference on Eyetracking and Applied Linguistics (ICEAL) was to bring together researchers who use eyetracking to empirically answer their research questions. It was intended to bridge the gaps between applied linguistics, translation studies, cognitive science and computational linguistics on the one hand and to further encourage innovative research methodologies and data triangulation on the other hand. These challenges are also addressed in this proceedings volume: While the studies described in the volume deal with a wide range of topics, they all agree on eyetracking as an appropriate methodology in empirical research

Independent spatiotemporal effects of spatial attention and background clutter on human object location representations

Spatial attention helps us to efficiently localize objects in cluttered environments. However, the processing stage at which spatial attention modulates object location representations remains unclear. Here we investigated this question identifying processing stages in time and space in an EEG and fMRI experiment respectively. As both object location representations and attentional effects have been shown to depend on the background on which objects appear, we included object background as an experimental factor. During the experiments, human participants viewed images of objects appearing in different locations on blank or cluttered backgrounds while either performing a task on fixation or on the periphery to direct their covert spatial attention away or towards the objects. We used multivariate classification to assess object location information. Consistent across the EEG and fMRI experiment, we show that spatial attention modulated location representations during late processing stages (>150 ms, in middle and high ventral visual stream areas) independent of background condition. Our results clarify the processing stage at which attention modulates object location representations in the ventral visual stream and show that attentional modulation is a cognitive process separate from recurrent processes related to the processing of objects on cluttered backgrounds

Drivers use active gaze to monitor waypoints during automated driving

Peer reviewe

Snap, Pursuit and Gain : Virtual Reality Viewport Control by Gaze

Head-mounted displays let users explore virtual environments through a viewport that is coupled with head movement. In this work, we investigate gaze as an alternative modality for viewport control, enabling exploration of virtual worlds with less head movement. We designed three techniques that leverage gaze based on different eye movements: Dwell Snap for viewport rotation in discrete steps, Gaze Gain for amplified viewport rotation based on gaze angle, and Gaze Pursuit for central viewport alignment of gaze targets. All three techniques enable 360-degree viewport control through naturally coordinated eye and head movement. We evaluated the techniques in comparison with controller snap and head amplification baselines, for both coarse and precise viewport control, and found them to be as fast and accurate. We observed a high variance in performance which may be attributable to the different degrees to which humans tend to support gaze shifts with head movement