Crossmodal content binding in information-processing architectures

Operating in a physical context, an intelligent robot faces two fundamental problems. First, it needs to combine information from its different sensors to form a representation of the environment that is more complete than any of its sensors on its own could provide. Second, it needs to combine high-level representations (such as those for planning and dialogue) with its sensory information, to ensure that the interpretations of these symbolic representations are grounded in the situated context. Previous approaches to this problem have used techniques such as (low-level) information fusion, ontological reasoning, and (high-level) concept learning. This paper presents a framework in which these, and other approaches, can be combined to form a shared representation of the current state of the robot in relation to its environment and other agents. Preliminary results from an implemented system are presented to illustrate how the framework supports behaviours commonly required of an intelligent robot

Revealing Perceptual Proxies in Comparative Data Visualization

Data Visualization has long been shaped by empirical evidence of the efficacies of different encodings, such as length, position, or area, in conveying quantities. Less is known, however, about what may affect comparison of multiple data series, which generally involves extraction of higher-order values, such as means, ranges, and correlations. In this work, we investigate such factors and the underlying visual processes that may account for them. We begin with a case study motivating the research, in which we modify Krona, a Bioinformatics visualization system, to support several types of comparison. Next, we empirically examine the influence of “arrangement”—that is, whether charts are shown side-by-side, stacked vertically, overlaid, etc.—on comparative tasks, in a series of psychophysical experiments. The results suggest a complex interaction of factors, with different comparative arrangements providing benefits for different combinations of tasks and encodings. For example, overlaid charts make detecting differences easier but comparing means or ranges more difficult. While these results offer some guidance to designers, the number of interactions makes it infeasible to provide broad rankings of arrangements, as has been done previously for encodings. Our subsequent efforts thus work toward understanding the visual processes that underlie the extraction of statistical summaries needed for comparison. It has recently been proposed that simpler shortcuts, called Perceptual Proxies, are used by the visual system to estimate these values. We investigate proxies for bar charts in experiments using an “adversarial” framework, in which the ranking of two charts along a task metric (e.g. mean) is opposite their ranking along a proxy metric (e.g. convex hull area). The strongest evidence we find is for use of a “centroid” proxy to estimate means in bar charts. Finally, we attempt to use using human-guided optimization to construct charts de novo, without assuming specific proxies. This work contributes both to perceptual psychology, by offering evidence for underlying visual processes that may be involved in the interpretation of comparative visualizations, and to data visualization, by providing new research methods and straightforward design guidance on how best to lay out charts to support certain tasks

Pervasive and standalone computing: The perceptual effects of variable multimedia quality.

The introduction of multimedia on pervasive and mobile communication devices raises a number of perceptual quality issues, however, limited work has been done examining the 3-way interaction between use of equipment, quality of perception and quality of service. Our work measures levels of informational transfer (objective) and user satisfaction (subjective)when users are presented with multimedia video clips at three different frame rates, using four different display devices, simulating variation in participant mobility. Our results will show that variation in frame-rate does not impact a user’s level of information assimilation, however, does impact a users’ perception of multimedia video ‘quality’. Additionally, increased visual immersion can be used to increase transfer of video information, but can negatively affect the users’ perception of ‘quality’. Finally, we illustrate the significant affect of clip-content on the transfer of video, audio and textual information, placing into doubt the use of purely objective quality definitions when considering multimedia presentations

On Face Segmentation, Face Swapping, and Face Perception

We show that even when face images are unconstrained and arbitrarily paired, face swapping between them is actually quite simple. To this end, we make the following contributions. (a) Instead of tailoring systems for face segmentation, as others previously proposed, we show that a standard fully convolutional network (FCN) can achieve remarkably fast and accurate segmentations, provided that it is trained on a rich enough example set. For this purpose, we describe novel data collection and generation routines which provide challenging segmented face examples. (b) We use our segmentations to enable robust face swapping under unprecedented conditions. (c) Unlike previous work, our swapping is robust enough to allow for extensive quantitative tests. To this end, we use the Labeled Faces in the Wild (LFW) benchmark and measure the effect of intra- and inter-subject face swapping on recognition. We show that our intra-subject swapped faces remain as recognizable as their sources, testifying to the effectiveness of our method. In line with well known perceptual studies, we show that better face swapping produces less recognizable inter-subject results. This is the first time this effect was quantitatively demonstrated for machine vision systems