The accuracy of pedometry varies depending on where an inertial sensor is located on the body. Motivated by the increasing popularity of wearable computing, this paper investigates the accuracy with which pedometry can be achieved on a head-mounted device: something previous research has not investigated. A study with 16 subjects compares the accuracy of pedometry for walking and running with an inertial sensor located at the head, pocket and hand/arm. Our study did not detect a significant difference in step counting accuracy between sensor locations, which demonstrates the feasibility of pedometry-based apps for head-mounted displays.

The availability of low-cost virtual reality (VR) systems coupled with a growing population of researchers accustomed to newer interface styles makes this a ripe time to help domain science researchers cross the bridge to utilizing immersive interfaces. The logical next step is for scientists, engineers, doctors, etc. to incorporate immersive visualization into their exploration and analysis workflows. However, from past experience, we know having access to equipment is not sufficient. There are also several software hurdles to overcome. Obstacles must be lowered to provide scientists, engineers, and medical professionals low-risk means of exploring technologies beyond their desktops.

Civil Support Teams (CST) must be ready to respond to a variety of potential situations involving dangerous materials. For many of these materials, standard real-world training methods can be successfully employed. Training involving radiological agents, however, poses a greater challenge than for other agents due to a lack of materials that can suitably mimic the situation without the danger of the real material. To address the need of providing a good training system for learning how to behave when responding to a radiological threat, we have developed a CST immersive training system. Our system simulates a radiological threat in a virtual environment and allows users to practice surveying the threat using virtual representations of the world and necessary equipment. We developed novel multi-user interaction techniques to enable simultaneous training for two CST members. The 92ndCST tested the system and provided feedback throughout the development process. The team learned to use the system with little coaching, quickly learned to navigate and interact via wand controls, and ultimately performed a successful demonstration of a radiological survey using our system for their superior officers.

We propose an acceleration scheme for many-body dynamic collision detection at interactive rates. We use the Velocity-Aligned Discrete Oriented Politope (VADOP), a tight bounding volume representation that offers fast update rates and which is particularly suitable for applications with many fast-moving objects. The axes selection that determines the shape of our bounding volumes is based on spherical coverings. We demonstrate that we can robustly detect collisions that are missed by pseudo-dynamic collision detection schemes, with even greater performance due to substantial collision pruning by our bounding volumes.

We present an event-based scheduling method for time-critical collision detection that meets real-time constraints by balancing and prioritizing computation spent on inter-section tests without starvation. We test each potentially colliding pair of objects at a different frequency, with un-bounded temporal resolution. We show that believability is preserved by adaptively prioritizing intersection tests to re-duce errors in collision detection, using information about the objects and scene. Through the combination of kinetic sweep and prune with stride scheduling we continuously interleave rendering, broad phase collision pruning, nar-row phase intersection testing, and collision response. Our method accrues no per-frame overhead and is interruptible at any point in collision detection, even the broad phase. 1