237 research outputs found

    For efficient navigational search, humans require full physical movement but not a rich visual scene

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    During navigation, humans combine visual information from their surroundings with body-based information from the translational and rotational components of movement. Theories of navigation focus on the role of visual and rotational body-based information, even though experimental evidence shows they are not sufficient for complex spatial tasks. To investigate the contribution of all three sources of information, we asked participants to search a computer generated “virtual” room for targets. Participants were provided with either only visual information, or visual supplemented with body-based information for all movement (walk group) or rotational movement (rotate group). The walk group performed the task with near-perfect efficiency, irrespective of whether a rich or impoverished visual scene was provided. The visual-only and rotate groups were significantly less efficient, and frequently searched parts of the room at least twice. This suggests full physical movement plays a critical role in navigational search, but only moderate visual detail is required

    Movement around real and virtual cluttered environments

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    Two experiments investigated participants’ ability to search for targets in a cluttered small-scale space. The first experiment was conducted in the real world with two field of view conditions (full vs. restricted), and participants found the task trivial to perform in both. The second experiment used the same search task but was conducted in a desktop virtual environment (VE), and investigated two movement interfaces and two visual scene conditions. Participants restricted to forward only movement performed the search task quicker and more efficiently (visiting fewer targets) than those who used an interface that allowed more flexible movement (forward, backward, left, right, and diagonal). Also, participants using a high fidelity visual scene performed the task significantly quicker and more efficiently than those who used a low fidelity scene. The performance differences between all the conditions decreased with practice, but the performance of the best VE group approached that of the real-world participants. These results indicate the importance of using high fidelity scenes in VEs, and suggest that the use of a simple control system is sufficient for maintaining ones spatial orientation during searching

    Movement around real and virtual cluttered environments

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    Two experiments investigated participants’ ability to search for targets in a cluttered small-scale space. The first experiment was conducted in the real world with two field of view conditions (full vs. restricted), and participants found the task trivial to perform in both. The second experiment used the same search task but was conducted in a desktop virtual environment (VE), and investigated two movement interfaces and two visual scene conditions. Participants restricted to forward only movement performed the search task quicker and more efficiently (visiting fewer targets) than those who used an interface that allowed more flexible movement (forward, backward, left, right, and diagonal). Also, participants using a high fidelity visual scene performed the task significantly quicker and more efficiently than those who used a low fidelity scene. The performance differences between all the conditions decreased with practice, but the performance of the best VE group approached that of the real-world participants. These results indicate the importance of using high fidelity scenes in VEs, and suggest that the use of a simple control system is sufficient for maintaining ones spatial orientation during searching

    Changes in navigational behaviour produced by a wide field of view and a high fidelity visual scene

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    The difficulties people frequently have navigating in virtual environments (VEs) are well known. Usually these difficulties are quantified in terms of performance (e.g., time taken or number of errors made in following a path), with these data used to compare navigation in VEs to equivalent real-world settings. However, an important cause of any performance differences is changes in people’s navigational behaviour. This paper reports a study that investigated the effect of visual scene fidelity and field of view (FOV) on participants’ behaviour in a navigational search task, to help identify the thresholds of fidelity that are required for efficient VE navigation. With a wide FOV (144 degrees), participants spent significantly larger proportion of their time travelling through the VE, whereas participants who used a normal FOV (48 degrees) spent significantly longer standing in one place planning where to travel. Also, participants who used a wide FOV and a high fidelity scene came significantly closer to conducting the search "perfectly" (visiting each place once). In an earlier real-world study, participants completed 93% of their searches perfectly and planned where to travel while they moved. Thus, navigating a high fidelity VE with a wide FOV increased the similarity between VE and real-world navigational behaviour, which has important implications for both VE design and understanding human navigation. Detailed analysis of the errors that participants made during their non-perfect searches highlighted a dramatic difference between the two FOVs. With a narrow FOV participants often travelled right past a target without it appearing on the display, whereas with the wide FOV targets that were displayed towards the sides of participants overall FOV were often not searched, indicating a problem with the demands made by such a wide FOV display on human visual attention

    Blue Line Mastermind

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    Battle Ready

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    Three levels of metric for evaluating wayfinding

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    Three levels of virtual environment (VE) metric are proposed, based on: (1) users’ task performance (time taken, distance traveled and number of errors made), (2) physical behavior (locomotion, looking around, and time and error classification), and (3) decision making (i.e., cognitive) rationale (think aloud, interview and questionnaire). Examples of the use of these metrics are drawn from a detailed review of research into VE wayfinding. A case study from research into the fidelity that is required for efficient VE wayfinding is presented, showing the unsuitability in some circumstances of common metrics of task performance such as time and distance, and the benefits to be gained by making fine-grained analyses of users’ behavior. Taken as a whole, the article highlights the range of techniques that have been successfully used to evaluate wayfinding and explains in detail how some of these techniques may be applied

    From the Whitt to Wall Street

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    Breaking Ground

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    From Wildcat D-Man to P-Bruins Head Coach

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