Efficient and precise interactive hand tracking through joint, continuous optimization of pose and correspondences

Fully articulated hand tracking promises to enable fundamentally new interactions with virtual and augmented worlds, but the limited accuracy and efficiency of current systems has prevented widespread adoption. Today's dominant paradigm uses machine learning for initialization and recovery followed by iterative model-fitting optimization to achieve a detailed pose fit. We follow this paradigm, but make several changes to the model-fitting, namely using: (1) a more discriminative objective function; (2) a smooth-surface model that provides gradients for non-linear optimization; and (3) joint optimization over both the model pose and the correspondences between observed data points and the model surface. While each of these changes may actually increase the cost per fitting iteration, we find a compensating decrease in the number of iterations. Further, the wide basin of convergence means that fewer starting points are needed for successful model fitting. Our system runs in real-time on CPU only, which frees up the commonly over-burdened GPU for experience designers. The hand tracker is efficient enough to run on low-power devices such as tablets. We can track up to several meters from the camera to provide a large working volume for interaction, even using the noisy data from current-generation depth cameras. Quantitative assessments on standard datasets show that the new approach exceeds the state of the art in accuracy. Qualitative results take the form of live recordings of a range of interactive experiences enabled by this new approach.

Handedness and social anxiety: using Bryden's research as a catalyst to explore the influence of familial sinistrality and degree of handedness

Phil Bryden's work has impacted on many areas of laterality, including degree and measurement of hand preference, as well as influences of familial sinistrality (FS). For example, Bryden[(1977). Measuring handedness with questionnaires. Neuropsychologia, 15, 617–624] is a well-cited and influential paper that remains relevant to this day. Inspired by this we extended our analysis of the relationship between handedness and anxiety in a number of ways. We used familial handedness and strength of handedness to examine their potential influences on anxiety, and extended our research by exploring their relationship to social anxiety, using the Social Phobia Inventory (SPIN). Inconsistent left-handers (ILH) were found to be more socially anxious. In all categories of SPIN except avoidance, ILH were significantly more anxious than consistent right- and left-handers. There were FS differences between ILH with a first degree left-handed relative (FS+) compared to ILH with no first degree left-handed relative (FS−) on all categories of anxiety scores. Within FS+ participants, ILH had significantly higher anxiety scores, compared with consistent handers across all categories. This suggests that ILH's social anxiety may be influenced by a close left-handed relative. Inspired by examining Bryden's work for this special issue, we will continue to add both strength of preference and familial handedness to our work.