Joseph M. Burling

Highlighting: A Mechanism Relevant for Word Learning

What we attend to at any moment determines what we learn at that moment, and this also depends on our past learning. This focused conceptual paper concentrates on a single well-documented attention mechanism – highlighting. This phenomenon – well studied in non-linguistic but not in linguistic contexts – should be highly relevant to language learning because it is a process that (1) specifically protects past learning from being disrupted by new (and potentially spurious) associations in the learning environment, and (2) strongly constrains new learning to new information. Within the language learning context, highlighting may disambiguate ambiguous references and may be related to processes of lexical competition that are known to be critical to on-line sentence comprehension. The main sections of the paper will address (1) the highlighting phenomenon in the literature; (2) its relevancy to language learning; (3) the highlighting effect in children; (4) developmental studies concerning the effect in different contexts; and (5) a developmental mechanism for highlighting in language learning.

A Semi-automated Method for Object Segmentation in Infant’s Egocentric Videos to Study Object Perception

Object segmentation in infant’s egocentric videos is a fundamental step in studying how children perceive objects in early stages of development. From the computer vision perspective, object segmentation in such videos poses quite a few challenges because the child’s view is unfocused, often with large head movements, effecting in sudden changes in the child’s point of view which leads to frequent change in object properties such as size, shape and illumination. In this paper, we develop a semi-automated, domain specific method, to address these concerns and facilitate the object annotation process for cognitive scientists, allowing them to select and monitor the object under segmentation. The method starts with an annotation of the desired object by user and employs graph cut segmentation and optical flow computation to predict the object mask for subsequent video frames automatically. To maintain accurate segmentation of objects, we use domain specific heuristic rules to re-initialize the program with new user input whenever object properties change dramatically. The evaluations demonstrate the high speed and accuracy of the presented method for object segmentation in voluminous egocentric videos. We apply the proposed method to investigate potential patterns in object distribution in child’s view at progressive ages.

Special session: Dynamic interactions between visual experiences, actions and word learning

The primary aim of this special session is to inform the conferences interdisciplinary audience about the state-of-the-art in developmental studies of action and language interactions. Action and language develop in parallel, impacting each other, and as such, bootstrap action, social, and cognitive development. We will present recent empirical evidence on developmental dependencies between visual experiences and word learning, followed by discussion of potential implications of this research for embodied theories of action and language integration.