Step synchronization and third person speed perception in virtual environment locomotion simulators

Human locomotion is known to be influenced by observation of another person's gait. For example, athletes often synchronize their step in long distance races. However, how interaction with a virtual runner affects the gait of a real runner has not been studied. We investigated this by creating an illusion of running behind a virtual model (VM) using a treadmill and large screen virtual environment showing a video of a VM. We looked at step synchronization between the real and virtual runner and at the role of the step frequency (SF) in the real runner's perception of VM speed. We found that subjects match VM SF when asked to match VM speed with their own (Figure 1). This indicates step synchronization may be a strategy of speed matching or speed perception. Subjects chose higher speeds when VMSF was higher (though VM was 12km/h in all videos). This effect was more pronounced when the speed estimate was rated verbally while standing still. (Figure 2). This may due to correlated physical activity affecting the perception of VM speed [Jacobs et al. 2005]; or step synchronization altering the subjects' perception of self speed [Durgin et al. 2007]. Our findings indicate that third person activity in a collaborative virtual locomotive environment can have a pronounced effect on an observer's gait activity and their perceptual judgments of the activity of others: the SF of others (virtual or real) can potentially influence one's perception of self speed and lead to changes in speed and SF. A better understanding of the underlying mechanisms would support the design of more compelling virtual trainers and may be instructive for competitive athletics in the real world. © 2009 ACM.

Foot contact detection for sprint training

We introduce a new algorithm to automatically identify the time and pixel location of foot contact events in high speed video of sprinters. We use this information to autonomously synchronise and overlay multiple recorded performances to provide feedback to athletes and coaches during their training sessions. The algorithm exploits the variation in speed of different parts of the body during sprinting. We use an array of foreground accumulators to identify short-term static pixels and a temporal analysis of the associated static regions to identify foot contacts. We evaluated the technique using 13 videos of three sprinters. It successfully identifed 55 of the 56 contacts, with a mean localisation error of 1.39±1.05 pixels. Some videos were also seen to produce additional, spurious contacts. We present heuristics to help identify the true contacts. © 2011 Springer-Verlag Berlin Heidelberg.

Towards real-time profiling of sprints using wearable pressure sensors

On-body sensor systems for sport are challenging since the sensors must be lightweight and small to avoid discomfort, and yet robust and highly accurate to withstand and capture the fast movements associated with sport. In this work, we detail our experience of building such an on-body system for track athletes. The paper describes the design, implementation and deployment of an on-body sensor system for sprint training sessions. We autonomously profile sprints to derive quantitative metrics to improve training sessions. Inexpensive Force Sensitive Resistors (FSRs) are used to capture foot events that are subsequently analysed and presented back to the coach. We show how to identify periods of sprinting from the FSR data and how to compute metrics such as ground contact time. We evaluate our system using force plates and show that millisecond-level accuracy is achievable when estimating contact times. © 2012 Elsevier B.V. All rights reserved.