This research explores the effect of symbology placement on human performance for users of head-mounted augmented reality displays. A pair of experiments examined the impact on visual performance asymmetries when perceiving complex, meaningful visual stimuli, such as the Arc Segment Attitude Reference (ASAR). The ASAR symbology represents an aircraft's vertical flight path and roll angles. Experiment 1 examined participants' performance in making categorical and coordinate judgments regarding various attitudes of the ASAR and a Gabor patch which were briefly presented in the peripheral visual field. The results were consistent with the horizontal-vertical anisotropy literature, which implies that performance would be better for stimuli placed on the horizontal than the vertical meridian. Experiment 2 assessed asymmetries for continuously presented stimuli in a dual-task environment which involved a centrally located, demanding visual psychomotor task and moni-toring of the ASAR or Gabor stimuli at the same peripheral locations as Experiment 1. No performance differ-ences were found as a function of peripheral stimulus placement. However, eye tracking, particularly for a subset of the participants suggest they employed a more efficient visual process to monitor the peripheral stimuli when the stimuli were placed on the horizontal meridian.

The proliferation of higher quality connected sensors is consistently increasing the amount of information available to operators, increasing the complexity of displayed information. Coupling this increase in information with larger, higher addressability displays may lead to increasingly complex visual search paradigms. The current research explored the effect of both display size and distractor symbol complexity on visual search efficiency across three different symbol set sizes. Overall, the results indicate a reduction in search efficiency as a function of both increased display size and distractor complexity, even for the high target densities employed within this study. Further, these variables can interact in target present conditions to influence search times.

To maximize visualization effectiveness, graphical data are commonly augmented with text to provide detailed information and define specific values. This text is often displayed in a pop-up dialog box pertaining to an object, permitting simultaneous display of the object and associated alphanumeric information. However, a human operator performance cost may be incurred when the resulting portrayal occludes critical information within the visualization. To address this issue, we developed and evaluated three alternative, spatially constrained, text portrayal techniques. These techniques and their associated access interface were designed to reduce occlusion while providing rapid access to desired alphanumeric data. Each technique was evaluated against the pop-up dialog using a dual-task human performance paradigm. Performance measures included accuracy, response time, display occlusion, and subjective feedback. The basis for the spatially-constrained text access technique design, their implementation affordances, and limitations are discussed. The alternative techniques and their user interface concepts resulted in mixed accuracy and response time performance compared to the pop-up dialog. Specific design features reduced data access time to one third of the time required to access the spatially-constrained text access techniques. Overall, equivalent performance was obtained among the variants while the potential for occlusion was reduced during use of the novel designs.

The dual-task paradigm methodology is a widely accepted approach to facilitate relative human performance measurement in a variety of tasks. The present paper describes the development and experimental validation of a visual-psychomotor secondary task. This task is proposed as a standardised secondary task set to facilitate human performance measurement during the objective evaluation of alternate primary tasks. The development of the secondary task is aligned with attributes suggested within the existing literature. The methodology is offered as a systematically derived secondary task with a tuned difficulty level which is intended to avoid floor or ceiling effects. Also, the data presented here afford the reader the ability to manipulate difficulty with known effect, if desired. Future plans include use of the secondary task set to facilitate a comparison of primary task independent variables. This activity will act to further exercise the potential utility of this ‘standardised’ secondary task and its associated mechanisation.

This chapter discusses concepts and tools for the exploration and visualization of computer-mediated communication (CMC), especially communication involving multiple users and taking place asynchronously. The work presented here is based on experimentally validated social networks (SN) extraction methods and consists of a diverse number of techniques for conveying the data to a business analyst. The chapter explores a large number of contexts ranging from direct social network graphs to more complex geographical, hierarchical, and conversation-centric approaches. User validation studies were conducted for the most representative techniques, centered both on extracting and on conveying of CMC data. The chapter examines methods for automatically extracting social networks, which is determining who is communicating with whom across different CMC channels. Beyond the network, the chapter focuses on the end-user discovery of topics and on integrating those with geographical, hierarchical, and user data. User-centric, interactive visualizations are presented from a functional perspective.

In applying the Arc-Segmented Attitude Reference (ASAR) symbology in headmounted displays (HMDs), it is uncertain if there is an optimal position for the symbology within the display. Vision science literature regarding visual asymmetries suggests that performance may differ depending upon the combination of the location of this symbology within the visual field and whether the user is interpreting the symbology to make categorical judgments (e.g., is the aircraft rolling left or right?) or coordinate judgments (e.g., what is the aircraft’s roll angle). Participants were asked to report aircraft roll and climb/dive angles of briefly presented ASAR symbology within the peripheral visual field on a monitor. There were no performance differences between the left and right ASAR positions in either the coordinate or categorical tasks. There were however trends consistent with horizontal-vertical anisotropy.

Objective: To evaluate a new display format for Airdrop Guidance intended to enhance precision-flight capability for high-altitude single-pass airdrop profiles.Background: Operational military environments are demanding that airdrops are increasingly precise while simultaneously protecting Air Force assets through high-altitude drops. Efforts are underway at the Air Force Research Laboratory to minimize the negative effect of human performance variability on high-altitude airdrop accuracy. Precision guidance to the calculated air release point, as presented through the new display, offers potential reduction in flight performance variability.Method: Four U.S. Air Force pilots, current in the C-17, participated in a within-subjects evaluation of the airdrop guidance display. Each pilot was scheduled to fly a total of 16 trials. The out-the-window scene (presented or blanked) effects were also assessed.Results: Results suggest improved performance over existing methods of airdrop guidance as measured by both aircraft position at green light and the comparison between actual and optimal flightpaths.Conclusion: The airdrop guidance display format, tested for precision flight, could significantly reduce flight performance error associated with high-altitude airdrop missions. Additionally, implementation of the display shows potential for increasing overall airdrop accuracy.

To answer the question: "what is 3D good for?" we reviewed the body of literature concerning the performance implications of stereoscopic 3D (S3D) displays versus non-stereo (20 or monoscopic) displays. We summarized results of over 160 publications describing over 180 experiments spanning 51 years of research in various fields including human factors psychology/engineering, human-computer interaction, vision science, visualization, and medicine. Publications were included if they described at least one task with a performance-based experimental evaluation of an S3D display versus a non-stereo display under comparable viewing conditions. We classified each study according to the experimental task(s) of primary interest: (a) judgments of positions and/or distances; (b) finding, identifying, or classifying objects; (c) spatial manipulations of real or virtual objects; (d) navigation; (e) spatial understanding, memory, or recall and (f) learning, training, or planning. We found that S3D display viewing improved performance over traditional non-stereo (2D) displays in 60% of the reported experiments. In 15% of the experiments, S3D either showed a marginal benefit or the results were mixed or unclear. In 25% of experiments, S3D displays offered no benefit over non-stereo 20 viewing (and in some rare cases, harmed performance). From this review, stereoscopic 3D displays were found to be most useful for tasks involving the manipulation of objects and for finding/identifying/classifying objects or imagery. We examine instances where S3D did not support superior task performance. We discuss the implications of our findings with regard to various fields of research concerning stereoscopic displays within the context of the investigated tasks. Published by Elsevier B.V.

With the growing number of image-producing sensors in different spectral bands it is often desirable to provide the operational community with an estimation of the level of target acquisition/recognition performance that could be expected for specific scenarios using these sensors. Many target acquisition/recognition models have been developed over the decades to try and predict expected human performance under various conditions. Many of these are relatively complicated and often concentrate on specific aspects, such as search strategies, atmospherics, or sensor parameters while ignoring other factors. This paper describes the development of a simple, high-level target acquisition/recognition model for predicting human performance for a particular class of operationally relevant, time-based scenarios involving sensor-aided viewing. Assumptions and relevant factors considered in developing the model are discussed and the model, in different forms, is presented. Fundamentally, the model is based on previously-collected human visual performance data using images of the Landolt C acuity target recorded using a short-wave infrared sensor, the Johnny Johnson target recognition criteria, and basic scenario parameters. Limited real-world testing of the model has been accomplished.

This work reviews the human factors-related literature on the task performance implications of stereoscopic 3D displays, in order to point out the specific performance benefits (or lack thereof) one might reasonably expect to observe when utilizing these displays. What exactly is 3D good for? Relative to traditional 2D displays, stereoscopic displays have been shown to enhance performance on a variety of depth-related tasks. These tasks include judging absolute and relative distances, finding and identifying objects (by breaking camouflage and eliciting perceptual "pop-out"), performing spatial manipulations of objects (object positioning, orienting, and tracking), and navigating. More cognitively, stereoscopic displays can improve the spatial understanding of 3D scenes or objects, improve memory/recall of scenes or objects, and improve learning of spatial relationships and environments. However, for tasks that are relatively simple, that do not strictly require depth information for good performance, where other strong cues to depth can be utilized, or for depth tasks that lie outside the effective viewing volume of the display, the purported performance benefits of 3D may be small or altogether absent. Stereoscopic 3D displays come with a host of unique human factors problems including the simulator-sickness-type symptoms of eyestrain, headache, fatigue, disorientation, nausea, and malaise, which appear to effect large numbers of viewers (perhaps as many as 25% to 50% of the general population). Thus, 3D technology should be wielded delicately and applied carefully; and perhaps used only as is necessary to ensure good performance.

Social network analysis is a powerful tool used to help analysts discover relationships amongst groups of people as well as individuals. It is the mathematics behind such social networks as Facebook and MySpace. These networks alone cause a huge amount of data to be generated and the issue is only compounded once one adds in other electronic media such as e-mails and twitter. In this paper we outline the basics of social network analysis and how it may be used in current and future Air Force applications.

As we near the ability in microdisplay technology development to surpass the resolution of the human eye, it is worth reviewing this remarkable sensor to better understand where future needs may be. In this paper we review the human eye and then compare current and future trending applications for helmet mounted displays. We aim to show best practices for development of new and innovative displays that work with the human rather than against the human.

SPIE Digital Library Proceedings.

Ensuring the proper and effective ways to visualize network data is important for many areas of academia, applied sciences, the military, and the public. Fields such as social network analysis, genetics, biochemistry, intelligence, cybersecurity, neural network modeling, transit systems, communications, etc. often deal with large, complex network datasets that can be difficult to interact with, study, and use. There have been surprisingly few human factors performance studies on the relative effectiveness of different graph drawings or network diagram techniques to convey information to a viewer. This is particularly true for weighted networks which include the strength of connections between nodes, not just information about which nodes are linked to other nodes. We describe a human factors study in which participants performed four separate network analysis tasks (finding a direct link between given nodes, finding an interconnected node between given nodes, estimating link strengths, and estimating the most densely interconnected nodes) on two different network visualizations: an adjacency matrix with a heat-map versus a node-link diagram. The results should help shed light on effective methods of visualizing network data for some representative analysis tasks, with the ultimate goal of improving usability and performance for viewers of network data displays.

Within an Air Operations Center (AOC), planners make crucial decisions to create the air plan for any given day. They are expected to complete the plan in part by pairing targeting or collection tasks with the available platforms. Any assistance these planners can acquire to help create the plan in a timely manner would make the entire process more efficient and effective. This paper describes the Intelligent Pairing Assistant (IPA) prototype, which would provide pairing recommendations at specific decision points in the planning process. IPA is designed as a plug-in for software systems already in use within AOCs. The primary contribution described in this paper is the application of existing research in intelligent user interfaces to a novel domain.

Identifying social network (SN) links within computer-mediated communication platforms without explicit relations among users poses challenges to researchers. Our research aims to extract SN links in internet chat with multiple users engaging in synchronous overlapping conversations all displayed in a single stream. We approached this problem using three methods which build on previous research. Response-time analysis builds on temporal proximity of chat messages; word context usage builds on keywords analysis and direct addressing which infers links by identifying the intended message recipient from the screen name (nickname) referenced in the message [1]. Our analysis of word usage within the chat stream also provides contexts for the extracted SN links. To test the capability of our methods, we used publicly available data from Internet Relay Chat (IRC), a real-time computer-mediated communication (CMC) tool used by millions of people around the world. The extraction performances of individual methods and their hybrids were assessed relative to a ground truth (determined a priori via manual scoring).

There has been significant research completed attempting to optimize the portrayal of ownship attitude information (OAI) via the Helmet-Mounted Display and, there has simultaneously been resistance by the user community regarding the inclusion of OAI. The stated reason is usually because they find it unnecessary. This paper includes a review of both sides of this discussion and attempts to make the case that, similar to the evolution of the Head-Up Display as a primary flight reference, there are likely operational performance and safety-of-flight reasons to justify off-axis OAI within even limited field-of-view applications.

Designers, researchers, and users of binocular stereoscopic head- or helmet-mounted displays (HMDs) face the tricky issue of what imagery to present in their particular displays, and how to do so effectively. Stereoscopic imagery must often be created in-house with a 3D graphics program or from within a 3D virtual environment, or stereoscopic photos/videos must be carefully captured, perhaps for relaying to an operator in a teleoperative system. In such situations, the question arises as to what camera separation (real or virtual) is appropriate or desirable for end-users and operators. We review some of the relevant literature regarding the question of stereo pair camera separation using deskmounted or larger scale stereoscopic displays, and employ our findings to potential HMD applications, including command & control, teleoperation, information and scientific visualization, and entertainment.

In virtual reality (VR) circles a "cave" is a 3 - 6 sided box with displays on each side. It has for many years sufficed as the "immersive" portion of VR mostly due to the insufficient head-mounted displays (HMDs) in the domain. However, current HMDs rival many caves and indeed are taking over. Here we discuss the pros and cons of this advent as well as human factors issues related to VR and the use of HMDs.

Recent years have brought on a new breed of HMDs. They have high resolution, are daylight readable, and some even have color. While these are all welcomed advances to the field we must remember to review our history. Here we review some the of the research from years past that was done before these advances and discuss them so as to make sure the past is not forgotten and mistakes are not repeated.