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Biomedical subjects

Jochen Triesch

Publications and source records attributed to Jochen Triesch.

5 recordsLinked to original sources

Gaze following: why (not) learn it?

We propose a computational model of the emergence of gaze following skills in infant-caregiver interactions. The model is based on the idea that infants learn that monitoring their caregiver's direction of gaze allows them to predict the locations of interesting objects or events in their environment (Moore & Corkum, 1994). Elaborating on this theory, we demonstrate that a specific Basic Set of structures and mechanisms is sufficient for gaze following to emerge. This Basic Set includes the infant's perceptual skills and preferences, habituation and reward-driven learning, and a structured social environment featuring a caregiver who tends to look at things the infant will find interesting. We review evidence that all elements of the Basic Set are established well before the relevant gaze following skills emerge. We evaluate the model in a series of simulations and show that it can account for typical development. We also demonstrate that plausible alterations of model parameters, motivated by findings on two different developmental disorders - autism and Williams syndrome - produce delays or deficits in the emergence of gaze following. The model makes a number of testable predictions. In addition, it opens a new perspective for theorizing about cross-species differences in gaze following.

Animals↗

Analysis of cluttered scenes using an elastic matching approach for stereo images.

We present a system for the automatic interpretation of cluttered scenes containing multiple partly occluded objects in front of unknown, complex backgrounds. The system is based on an extended elastic graph matching algorithm that allows the explicit modeling of partial occlusions. Our approach extends an earlier system in two ways. First, we use elastic graph matching in stereo image pairs to increase matching robustness and disambiguate occlusion relations. Second, we use richer feature descriptions in the object models by integrating shape and texture with color features. We demonstrate that the combination of both extensions substantially increases recognition performance. The system learns about new objects in a simple one-shot learning approach. Despite the lack of statistical information in the object models and the lack of an explicit background model, our system performs surprisingly well for this very difficult task. Our results underscore the advantages of view-based feature constellation representations for difficult object recognition problems.

Algorithms↗

Task demands control acquisition and storage of visual information.

Attention and working memory limitations set strict limits on visual representations, yet researchers have little appreciation of how these limits constrain the acquisition of information in ongoing visually guided behavior. Subjects performed a brick sorting task in a virtual environment. A change was made to 1 of the features of the brick being held on about 10% of trials. Rates of change detection for feature changes were generally low and depended on the pick-up and put-down relevance of the feature to the sorting task. Subjects' sorting decision suggests that changes may be missed because of a failure to update the changed feature. The authors also explore how hand and eye behavior are coordinated for strategic acquisition and storage of visual information throughout the task.

Adolescent↗

What you see is what you need.

We studied the role of attention and task demands for implicit change detection. Subjects engaged in an object sorting task performed in a virtual reality environment, where we changed the properties of an object while the subject was manipulating it. The task assures that subjects are looking at the changed object immediately before and after the change. Our results demonstrate that in this situation subjects' ability to notice changes to the object strongly depends on momentary task demands. Surprisingly, frequent noticing is not guaranteed by task relevance of the changed object attribute per se, but the changed object attribute needs to be task relevant at exactly the right times. Also, the simplicity of the used objects indicates that change blindness occurs in situations where the visual short term memory load is minimal, suggesting a potential dissociation between short term memory limitations and change blindness. Finally, we found that changes may even go unnoticed if subjects are visually tracking the object at the moment of change. Our experiments suggest a highly purposive and task specific nature of human vision, where information extracted from the fixation point is used for certain computations only "just in time" when needed to solve the current goal.

Attention↗

Fast temporal dynamics of visual cue integration.

The integration of information from different sensors, cues, or modalities lies at the very heart of perception. We are studying adaptive phenomena in visual cue integration. To this end, we have designed a visual tracking task, where subjects track a target object among distractors and try to identify the target after an occlusion. Objects are defined by three different attributes (color, shape, size) which change randomly within a single trial. When the attributes differ in their reliability (two change frequently, one is stable), our results show that subjects dynamically adapt their processing. The results are consistent with the hypothesis that subjects rapidly re-weight the information provided by the different cues by emphasizing the information from the stable cue. This effect seems to be automatic, ie not requiring subjects' awareness of the differential reliabilities of the cues. The hypothesized re-weighting seems to take place in about 1 s. Our results suggest that cue integration can exhibit adaptive phenomena on a very fast time scale. We propose a probabilistic model with temporal dynamics that accounts for the observed effect.

Adaptation, Psychological↗