Visual interaction with dimensionality reduction: a structured literature analysis

Dimensionality Reduction (DR) is a core building block in visualizing multidimensional data. For DR techniques to be useful in exploratory data analysis, they need to be adapted to human needs and domain-specific problems, ideally, interactively, and on-the-fly. Many visual analytics systems have already demonstrated the benefits of tightly integrating DR with interactive visualizations. Nevertheless, a general, structured understanding of this integration is missing. To address this, we systematically studied the visual analytics and visualization literature to investigate how analysts interact with automatic DR techniques. The results reveal seven common interaction scenarios that are amenable to interactive control such as specifying algorithmic constraints, selecting relevant features, or choosing among several DR algorithms. We investigate specific implementations of visual analysis systems integrating DR, and analyze ways that other machine learning methods have been combined with DR. Summarizing the results in a “human in the loop” process model provides a general lens for the evaluation of visual interactive DR systems. We apply the proposed model to study and classify several systems previously described in the literature, and to derive future research opportunities

Visual interaction with dimensionality reduction: a structured literature analysis

Dimensionality Reduction (DR) is a core building block in visualizing multidimensional data. For DR techniques to be useful in exploratory data analysis, they need to be adapted to human needs and domain-specific problems, ideally, interactively, and on-the-fly. Many visual analytics systems have already demonstrated the benefits of tightly integrating DR with interactive visualizations. Nevertheless, a general, structured understanding of this integration is missing. To address this, we systematically studied the visual analytics and visualization literature to investigate how analysts interact with automatic DR techniques. The results reveal seven common interaction scenarios that are amenable to interactive control such as specifying algorithmic constraints, selecting relevant features, or choosing among several DR algorithms. We investigate specific implementations of visual analysis systems integrating DR, and analyze ways that other machine learning methods have been combined with DR. Summarizing the results in a “human in the loop” process model provides a general lens for the evaluation of visual interactive DR systems. We apply the proposed model to study and classify several systems previously described in the literature, and to derive future research opportunities

Visual cognition during real social interaction

Copyright @ 2012 The Authors. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and 85 reproduction in any medium, provided the original author and source are credited. The article was made available through the Brunel University Open Access Publishing Fund.This article has been made available through the Brunel Open Access Publishing Fund.Laboratory studies of social visual cognition often simulate the critical aspects of joint attention by having participants interact with a computer-generated avatar. Recently, there has been a movement toward examining these processes during authentic social interaction. In this review, we will focus on attention to faces, attentional misdirection, and a phenomenon we have termed social inhibition of return (Social IOR), that have revealed aspects of social cognition that were hitherto unknown. We attribute these discoveries to the use of paradigms that allow for more realistic social interactions to take place. We also point to an area that has begun to attract a considerable amount of interest—that of Theory of Mind (ToM) and automatic perspective taking—and suggest that this too might benefit from adopting a similar approach

Subjective information visualizations

Information Visualizations (InfoViz) are systems that require high levels of cognitive processing. They revolve around the notion of decoding and interpreting visual patterns in order to achieve certain goals. We argue that purely designing for the visual will not allow for optimum experiences since there is more to InfoViz than just the visual. Interaction is a key to achieving higher levels of knowledge. In this position paper we present a different perspective on the underlying meaning of interaction, where we describe it as incorporating both the visual and the physical activities. By physical activities we mean the physical actions upon the physical input device/s. We argue that interaction is the key element for supporting users’ subjective experiences hence these experiences should first be understood. All the discussions in this paper are based upon on going work in the field of visualizing the literature knowledge domain (LKDViz)

Physics-based visual characterization of molecular interaction forces

Molecular simulations are used in many areas of biotechnology, such as drug design and enzyme engineering. Despite the development of automatic computational protocols, analysis of molecular interactions is still a major aspect where human comprehension and intuition are key to accelerate, analyze, and propose modifications to the molecule of interest. Most visualization algorithms help the users by providing an accurate depiction of the spatial arrangement: the atoms involved in inter-molecular contacts. There are few tools that provide visual information on the forces governing molecular docking. However, these tools, commonly restricted to close interaction between atoms, do not consider whole simulation paths, long-range distances and, importantly, do not provide visual cues for a quick and intuitive comprehension of the energy functions (modeling intermolecular interactions) involved. In this paper, we propose visualizations designed to enable the characterization of interaction forces by taking into account several relevant variables such as molecule-ligand distance and the energy function, which is essential to understand binding affinities. We put emphasis on mapping molecular docking paths obtained from Molecular Dynamics or Monte Carlo simulations, and provide time-dependent visualizations for different energy components and particle resolutions: atoms, groups or residues. The presented visualizations have the potential to support domain experts in a more efficient drug or enzyme design process.Peer ReviewedPostprint (author's final draft

Novel Multimodal Feedback Techniques for In-Car Mid-Air Gesture Interaction

This paper presents an investigation into the effects of different feedback modalities on mid-air gesture interaction for infotainment systems in cars. Car crashes and near-crash events are most commonly caused by driver distraction. Mid-air interaction is a way of reducing driver distraction by reducing visual demand from infotainment. Despite a range of available modalities, feedback in mid-air gesture systems is generally provided through visual displays. We conducted a simulated driving study to investigate how different types of multimodal feedback can support in-air gestures. The effects of different feedback modalities on eye gaze behaviour, and the driving and gesturing tasks are considered. We found that feedback modality influenced gesturing behaviour. However, drivers corrected falsely executed gestures more often in non-visual conditions. Our findings show that non-visual feedback can reduce visual distraction significantl

Trends and Techniques in Visual Gaze Analysis

Visualizing gaze data is an effective way for the quick interpretation of eye tracking results. This paper presents a study investigation benefits and limitations of visual gaze analysis among eye tracking professionals and researchers. The results were used to create a tool for visual gaze analysis within a Master's project.Comment: pages 89-93, The 5th Conference on Communication by Gaze Interaction - COGAIN 2009: Gaze Interaction For Those Who Want It Most, ISBN: 978-87-643-0475-

Smoothness perception : investigation of beat rate effect on frame rate perception

Despite the complexity of the Human Visual System (HVS), research over the last few decades has highlighted a number of its limitations. These limitations can be exploited in computer graphics to significantly reduce computational cost and thus required rendering time, without a viewer perceiving any difference in resultant image quality. Furthermore, cross-modal interaction between different modalities, such as the influence of audio on visual perception, has also been shown as significant both in psychology and computer graphics. In this paper we investigate the effect of beat rate on temporal visual perception, i.e. frame rate perception. For the visual quality and perception evaluation, a series of psychophysical experiments was conducted and the data analysed. The results indicate that beat rates in some cases do affect temporal visual perception and that certain beat rates can be used in order to reduce the amount of rendering required to achieve a perceptual high quality. This is another step towards a comprehensive understanding of auditory-visual cross-modal interaction and could be potentially used in high-fidelity interactive multi-sensory virtual environments

Atypical audiovisual speech integration in infants at risk for autism

The language difficulties often seen in individuals with autism might stem from an inability to integrate audiovisual information, a skill important for language development. We investigated whether 9-month-old siblings of older children with autism, who are at an increased risk of developing autism, are able to integrate audiovisual speech cues. We used an eye-tracker to record where infants looked when shown a screen displaying two faces of the same model, where one face is articulating/ba/and the other/ga/, with one face congruent with the syllable sound being presented simultaneously, the other face incongruent. This method was successful in showing that infants at low risk can integrate audiovisual speech: they looked for the same amount of time at the mouths in both the fusible visual/ga/− audio/ba/and the congruent visual/ba/− audio/ba/displays, indicating that the auditory and visual streams fuse into a McGurk-type of syllabic percept in the incongruent condition. It also showed that low-risk infants could perceive a mismatch between auditory and visual cues: they looked longer at the mouth in the mismatched, non-fusible visual/ba/− audio/ga/display compared with the congruent visual/ga/− audio/ga/display, demonstrating that they perceive an uncommon, and therefore interesting, speech-like percept when looking at the incongruent mouth (repeated ANOVA: displays x fusion/mismatch conditions interaction: F(1,16) = 17.153, p = 0.001). The looking behaviour of high-risk infants did not differ according to the type of display, suggesting difficulties in matching auditory and visual information (repeated ANOVA, displays x conditions interaction: F(1,25) = 0.09, p = 0.767), in contrast to low-risk infants (repeated ANOVA: displays x conditions x low/high-risk groups interaction: F(1,41) = 4.466, p = 0.041). In some cases this reduced ability might lead to the poor communication skills characteristic of autism