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Article Excerpt
INTRODUCTION
Three-dimensional virtual environments (VEs) and teleoperated systems are frequently characterized by the use of an egocentric viewpoint that moves through the environment, offering viewers multiple perspectives on a visual information display. Numerous applications have been developed that use VEs to allow exploration of real-world phenomena, including galaxies, molecules, architectural layouts, and battlefields (Hix et al., 1999). Teleoperation applications include terrestrial, undersea, and aerial robots as well as long-latency planetary rovers (Sheridan, 1992). Searching for and learning from objects in a VE or teleoperation requires both movement and control of gaze. Although people routinely scan their surroundings using eye and head movements as they walk, there are no corresponding natural movements of the viewpoint in desktop VE or teleoperation systems. As a consequence it is more difficult to search for objects and landmarks. This problem is exacerbated in teleoperation activities, which are also frequently constrained with a much narrower field of view. Although these reported experiments involve VEs, our results can be readily extended to teleoperation in which automatic target recognition or other feature detection information is available.
Whether the motivation is danger, cost, or constraints of the physical world, VEs are well suited to provide viewers with two types of information: survey knowledge (where things are) and object knowledge (what is there). Siegel and White (1975) identified survey knowledge as the ability to understand the global organizational structure of a collection of objects. Survey knowledge is often likened to having a mental representation of a map that allows viewers to mentally navigate the space. Although survey knowledge can be obtained solely by studying maps, a more thorough understanding can be achieved by actually navigating in the environment (Arthur, Hancock, & Telke, 1996; Thorndyke & Hayes-Roth, 1982). It is important to note that true navigation requires the active engagement of the viewer; it is not enough to automatically move a viewer through an environment as if on a tour bus. Peruch, Vercher, and Guthier (1995) determined that self-controlled viewers tended to develop a lich survey knowledge more quickly than did passive observers.
Helping users acquire object knowledge represents a challenge that is common to the design of all graphical displays: facilitating the viewer's ability to extract relevant information from the surrounding context. This is commonly known among visualization researchers as the "focus-plus-context" problem (Card, Mackinlay, & Shneiderman, 1999). This issue has been well researched in the domain of two-dimensional (2-D) displays. Many approaches to this issue allow the viewer to distort or magnify a portion of the display to allow for closer inspection (Keahey, 1998). Other methods attempt to provide visual cues to highlight or augment specific areas of interest (Zhai, Wright, Selker, & Kelin, 1997). Although these approaches work well if the important features are always within the field of view, they may not be suited to large VEs, in which part of the model can be occluded or otherwise out of sight. Furthermore, deliberately introducing distortions may impair the viewer's ability to gain accurate survey knowledge.
To locate objects in 3-D environments requires that (a) the viewer is positioned in a location from which the object can potentially be viewed, (b) the viewpoint is subsequently oriented such that the relevant objects are prominently displayed within the field of view, and (c) Objectives a and b are met while maintaining the spatial integrity of the environment. Unfortunately, this is a difficult task for a person to do alone. The operator is often faced with the cognitively demanding task of controlling six viewing parameters: position (x, y, z) and orientation (yaw, pitch, and roll). Arthur, Hancock, and Chrysler (1993) pointed out that "when interaction becomes highly attention demanding, memory for the present location frequently decays, with the result that the individual becomes lost in space" (p. 328). Moreover, Goerger et al. (1998) found that self-navigating viewers in information-rich VEs are particularly susceptible to superfluous data and are easily distracted. If viewers are left to control their own viewpoint, these distractions can significantly impair their ability to complete searching tasks.
Although motion through scenes is essential to both kinds of information, the amount of self-determination the viewer has over the viewpoint is critical. Survey knowledge flourishes when the viewer is able to freely explore the environment, but important details may be overlooked if guidance is not provided. Numerous methods have been developed for viewpoint control in VEs, but they tend to cater to one of two extremes. On one hand, guided navigation techniques automatically move the viewpoint through the environment, often relying on guidelines from cinematography to ensure that relevant imagery is presented from the model (Bares, Thainimit, & McDermott, 2000; Drucker & Zeltzer, 1994; Halper & Oliver, 2000; He, Cohen, & Salesin, 1996). On the other hand, research into free navigation attempts to minimize cognitive overhead and physical interaction in the hope that the viewer's resources will be more directed to positioning the viewpoint in meaningful locations. Several dominant metaphors for viewpoint control have emerged, including "eyeball in hand," "flying vehicle" (Ware & Osborne, 1990), and "gaze-directed steering" (Bowman, Koller, & Hodges, 1997).
These approaches present an all-or-nothing approach to the amount of self-determination that the viewer can exert when exploring the environment. Some recent investigations attempted to provide hybrid systems, allowing users to toggle between exploration and guided modes. Beckhaus, Ritter, and Strothotte (2001) described a guided tour system that can be interrupted to allow viewers to explore an area of local interest. When the viewer is finished, the tour is capable of automatically resuming from wherever the viewer left off.
Very little attention has been paid to the idea of partially automating viewpoint control to promote a supportive yet unscripted exploration of a virtual environment. This work explores this possibility through an approach known as attentive navigation. This technique for viewpoint motion grants the viewer an "appropriate" level of control while the system suggests optimal viewing parameters. The following sections of this paper discuss specific details of the interaction model and present the results of three experiments designed to evaluate the effectiveness of this technique for promoting spatial knowledge.
ATTENTIVE NAVIGATION
Attentive navigation attempts to reconcile the issues surrounding self-control in VEs by sharing control of the viewpoint between the viewer and the designer of the environment. The viewer effectively controls the position in the environment, and the system offers viewpoint suggestions based on the user's context within the environment. The self-determined motion allows the viewer to benefit from multiple orientations and receive the information on demand. At the same time, the technique can support the viewer's goals by focusing the viewpoint on elements of the scene that build knowledge while impeding perspectives that detract from learning.
Attentive navigation is an implementation of a method proposed by Hanson and Wernert (1997) in an attempt to facilitate 3-D navigation using 2-D controllers. Their technique divides the navigation space into two...
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