________________________________________________________________________This study investigated the effect of body-based information (proprioception, etc.) when participants navigated large-scale virtual marketplaces that were either small (Experiment 1) or large in extent (Experiment 2). Extent refers to the size of an environment, whereas scale refers to whether people have to travel through an environment to see the detail necessary for navigation. Each participant was provided with full body-based information (walking through the virtual marketplaces in a large tracking hall or on an omni-directional treadmill), just the translational component of body-based information (walking on a linear treadmill, but turning with a joystick), just the rotational component (physically turning but using a joystick to translate) or no body-based information (joysticks to translate and rotate). In large and small environments translational body-based information significantly improved the accuracy of participants' cognitive maps, measured using estimates of direction and relative straight line distance but, on its own, rotational body-based information had no effect. In environments of small extent, full body-based information also improved participants' navigational performance. The experiments show that locomotion devices such as linear treadmills would bring substantial benefits to virtual environment applications where large spaces are navigated, and theories of human navigation need to reconsider the contribution made by body-based information, and distinguish between environmental scale and extent.

Two experiments investigated the effects of landmarks and body-based information on route knowledge. Participants made four out-and-back journeys along a route, guided only on the first outward trip and with feedback every time an error was made. Experiment 1 used 3-D virtual environments (VEs) with a desktop monitor display, and participants were provided with no supplementary landmarks, only global landmarks, only local landmarks, or both global and local landmarks. Local landmarks significantly reduced the number of errors that participants made, but global landmarks did not. Experiment 2 used a headmounted display; here, participants who physically walked through the VE (translational and rotational body-based information) made 36% fewer errors than did participants who traveled by physically turning but changing position using a joystick. Overall, the experiments showed that participants were less sure of where to turn than which way, and journey direction interacted with sensory information to affect the number and types of errors participants made.

________________________________________________________________________This article provides longitudinal data for when participants learned to travel with a walking metaphor through virtual reality (VR) worlds, using interfaces that ranged from joystick-only, to linear and omnidirectional treadmills, and actual walking in VR. Three metrics were used: travel time, collisions (a measure of accuracy), and the speed profile. The time that participants required to reach asymptotic performance for traveling, and what that asymptote was, varied considerably between interfaces. In particular, when a world had tight turns (0.75 m corridors), participants who walked were more proficient than those who used a joystick to locomote and turned either physically or with a joystick, even after 10 minutes of training. The speed profile showed that this was caused by participants spending a notable percentage of the time stationary, irrespective of whether or not they frequently played computer games. The study shows how speed profiles can be used to help evaluate participants' proficiency with travel interfaces, highlights the need for training to be structured to addresses specific weaknesses in proficiency (e.g., start-stop movement), and for studies to measure and report that proficiency.

Emotion expression in human-human interaction takes place via various types of information, including body motion. Research on the perceptual-cognitive mechanisms underlying the processing of natural emotional body language can benefit greatly from datasets of natural emotional body expressions that facilitate stimulus manipulation and analysis. The existing databases have so far focused on few emotion categories which display predominantly prototypical, exaggerated emotion expressions. Moreover, many of these databases consist of video recordings which limit the ability to manipulate and analyse the physical properties of these stimuli. We present a new database consisting of a large set (over 1400) of natural emotional body expressions typical of monologues. To achieve close-to-natural emotional body expressions, amateur actors were narrating coherent stories while their body movements were recorded with motion capture technology. The resulting 3-dimensional motion data recorded at a high frame rate (120 frames per second) provides fine-grained information about body movements and allows the manipulation of movement on a body joint basis. For each expression it gives the positions and orientations in space of 23 body joints for every frame. We report the results of physical motion properties analysis and of an emotion categorisation study. The reactions of observers from the emotion categorisation study are included in the database. Moreover, we recorded the intended emotion expression for each motion sequence from the actor to allow for investigations regarding the link between intended and perceived emotions. The motion sequences along with the accompanying information are made available in a searchable MPI Emotional Body Expression Database. We hope that this database will enable researchers to study expression and perception of naturally occurring emotional body expressions in greater depth.