Visual Clutter Study for Pedestrian Using Large Scale Naturalistic Driving Data

Some of the pedestrian crashes are due to driver’s late or difficult perception of pedestrian’s appearance. Recognition of pedestrians during driving is a complex cognitive activity. Visual clutter analysis can be used to study the factors that affect human visual search efficiency and help design advanced driver assistant system for better decision making and user experience. In this thesis, we propose the pedestrian perception evaluation model which can quantitatively analyze the pedestrian perception difficulty using naturalistic driving data. An efficient detection framework was developed to locate pedestrians within large scale naturalistic driving data. Visual clutter analysis was used to study the factors that may affect the driver’s ability to perceive pedestrian appearance. The candidate factors were explored by the designed exploratory study using naturalistic driving data and a bottom-up image-based pedestrian clutter metric was proposed to quantify the pedestrian perception difficulty in naturalistic driving data. Based on the proposed bottom-up clutter metrics and top-down pedestrian appearance based estimator, a Bayesian probabilistic pedestrian perception evaluation model was further constructed to simulate the pedestrian perception process

An Augmentative Gaze Directing Framework for Multi-Spectral Imagery

Modern digital imaging techniques have made the task of imaging more prolic than ever and the volume of images and data available through multi-spectral imaging methods for exploitation is exceeding that which can be solely processed by human beings. The researchers proposed and developed a novel eye movement contingent framework and display system through adaption of the demonstrated technique of subtle gaze direction by presenting modulations within the displayed image. The system sought to augment visual search task performance of aerial imagery by incorporating multi-spectral image processing algorithms to determine potential regions of interest within an image. The exploratory work conducted was to study the feasibility of visual gaze direction with the specic intent of extending this application to geospatial image analysis without need for overt cueing to areas of potential interest and thereby maintaining the benefits of an undirected and unbiased search by an observer

THE EFFECTS OF ALTERNATE-LINE SHADING ON VISUAL SEARCH IN GRID-BASED GRAPHIC DESIGNS

Objective: The goal of this research was to determine whether alternate-line shading (zebra-striping) of grid-based displays affects the strategy (i.e., “visual flow”) and efficiency of serial search. Background: Grids, matrices, and tables are commonly used to organize information. A number of design techniques and psychological principles are relevant to how viewers’ eyes can be guided through such visual works. One common technique for grids, “zebra-striping,” is intended to guide eyes through the design, or “create visual flow” by alternating shaded and unshaded rows or columns. Method: 13 participants completed a visual serial search task. The target was embedded in a grid that had 1) no shading, 2) shading of alternating rows, or 3) shading of alternating columns. Response times and error rates were analyzed to determine search strategy and efficiency. Results: Our analysis found evidence supporting a weak effect of shading on search strategy. The direction of shading had an impact on which parts of the grid were responded to most rapidly. However, a left-to-right reading bias and middle-to-outside edge effect were also found. Overall performance was reliably better when the grid had no shading. Exploratory analyses suggest individual differences may be a factor. Conclusion: Shading seems to create visual flow that is relatively weak compared to search strategies related to the edge effect or left-to-right reading biases. In general, however, the presence of any type of shading reduced search performance. Application: Designers creating a grid-based display should not automatically assume that shading will change viewers search strategies. Furthermore, although strategic shading may be useful for tasks other than that studied here, our current data indicate that shading can actually be detrimental to visual search for complex (i.e., conjunctive) targets

Analyzing the Information Search Behavior and Intentions in Visual Information Systems

Visual information search systems support different search approaches such as targeted, exploratory or analytical search. Those visual systems deal with the challenge of composing optimal initial result visualization sets that face the search intention and respond to the search behavior of users. The diversity of these kinds of search tasks require different sets of visual layouts and functionalities, e.g. to filter, thrill-down or even analyze concrete data properties. This paper describes a new approach to calculate the probability towards the three mentioned search intentions, derived from users’ behavior. The implementation is realized as a web-service, which is included in a visual environment that is designed to enable various search strategies based on heterogeneous data sources. In fact, based on an entered search query our developed search intention analysis web-service calculates the most probable search task, and our visualization system initially shows the optimal result set of visualizations to solve the task. The main contribution of this paper is a probability-based approach to derive the users’ search intentions based on the search behavior enhanced by the application to a visual system

Interactive time series analytics powered by ONEX

Modern applications in this digital age collect a staggering amount of time series data from economic growth rates to electrical household consumption habits. To make sense of it, domain analysts interactively sift through these time series collections in search of critical relationships between and recurring patterns within these time series. The ONEX (Online Exploration of Time Series) system supports effective exploratory analysis of time series collections composed of heterogeneous, variable-length and misaligned time series using robust alignment dynamic time warping (DTW) methods. To assure real-time responsiveness even for these complex and compute-intensive analytics, ONEX precomputes and then encodes time series relationships based on the inexpensive-to-compute Euclidean distance into the ONEX base. Thereafter, based on a solid formal foundation, ONEX uses DTW-enhanced analytics to correctly extract relevant time series matches on this Euclidean-prepared ONEX base. Our live interactive demonstration shows how our ONEX exploratory tool, supported by a rich array of visual interactions and expressive visualizations, enables efficient mining and interpretation of the MATTERS real data collection composed of economic, social, and education data trends across the fifty American states. © 2017 ACM

Video game training in traumatic brain injury patients: an exploratory case report study using eye tracking

Remediation of attentional impairments is an essential component of cognitive rehabilitation after traumatic brain injury (TBI). Evidence from healthy participants has demonstrated attentional improvement following playing an action video game. This exploratory study investigated its application in TBI participants in a multiple baselines single case experimental design (SCED). Saccadic eye movements, recognized as the visible indicators of visual attention, were assessed to evaluate the effectiveness of the game training. Three severe TBI participants were trained in an action game for 10 hours. Saccadic eye movements during a self-paced saccade and an abstract visual search task were investigated during baseline, mid training and post-training. Using Percentage of Non-overlapping Data (PND), analysis showed consistent increase in the rate of the self-paced saccades in participants 1 (PND=80%) and 2 (PND=70%). In abstract search, fixation duration showed a minimally effective decrease for participant 2 (PND= 60%) and a moderately effective reduction in participant 3 (PND= 80%). Search time showed a highly effective reduction in participant 2 (PND = 100%) and moderately effective decrease in participant 3 (PND=70%). Overall, video game training might modify allocation of attention in eye movements. More evidence is required to validate the usefulness of this novel method of the cognitive training

A visual exploration workflow as enabler for the exploitation of Linked Open Data

Abstract. Semantically annotating and interlinking Open Data results in Linked Open Data which concisely and unambiguously describes a knowledge domain. However, the uptake of the Linked Data depends on its usefulness to non-Semantic Web experts. Failing to support data consumers to understand the added-value of Linked Data and possible exploitation opportunities could inhibit its diffusion. In this paper, we propose an interactive visual workflow for discovering and ex-ploring Linked Open Data. We implemented the workflow considering academic library metadata and carried out a qualitative evaluation. We assessed the work-flow’s potential impact on data consumers which bridges the offer: published Linked Open Data; and the demand as requests for: (i) higher quality data; and (ii) more applications that re-use data. More than 70 % of the 34 test users agreed that the workflow fulfills its goal: it facilitates non-Semantic Web experts to un-derstand the potential of Linked Open Data.