ISSN : 1796-2048
Volume : 1    Issue : 4    Date : July 2006

Robust Real-time 3D Detection of Obstructed Head and Hands in Indoors Environments
Sébastien Grange and Charles Baur  
Page(s): 29-36
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We address the need for robust detection of obstructed human features in complex environments,
with a focus on intelligent surgical UIs. In our setup, real-time detection is used to find features
without the help of local (spatial or temporal) information. Such a detector is used to validate, correct
or reject the output of the visual feature tracking, which is locally more robust, but drifts over time.
In Operating Rooms (OR), surgeons’ faces and hands are typically obstructed by sterile clothing
and tools, making statistical and/or feature-based feature detection approaches ineffective. We
propose a new method for head and hands detection that relies on geometric information from
disparity maps, locally refined by color processing. We have applied our method to a surgical mock-
up scene, as well as to images gathered during real surgery. Running in a realtime, continuous
detection loop, our detector successfully found more than 97% of target features, with very few false
positives (less than 0.7%).

Index Terms
medical interface, head and hands detection