| Summary: | The increased popularity of applications requiring head tracking, such as teleconferencing and
virtual reality, have fuelled research efforts to provide computer vision solutions to the problem
of real-time head movement tracking. The attractiveness of this type of solution rests on the fact
that head tracking can be performed without the use of expensive and cumbersome physical
devices.
We propose a computer vision approach that detects the head movements of a user seated at a
computer workstation. We model head translation and head rotation using distinct sets of
templates synthesized from an initially captured image of the head and representing this head in
various positions (and sizes) and orientations. Using correlation-based template matching, we
achieve detection by correlating these sets of templates against each image of the head captured
by a camera positioned on the top of the monitor. The best-correlating template from the set
modelling head translation and the best from the set modelling head rotation represent good
approximations of the three-dimensional position and orientation of the head in the scene,
respectively. We improve on these approximations by defining two functions that interpolate the
correlation scores of each set and by obtaining the minimum of each of these functions. We use
these two minima, which represent head position and orientation, to synthesize a new template
based on the initially captured image of the head. This new synthesized template represents the
image of the head that most closely approximates the head position and orientation in the scene.
Head movement tracking is performed by comparing the closest approximation of the head found
in two consecutive images of the scene.
We have implemented our head movement tracking approach and found our system to track head
position, on average, to within one pixel of the measured head position in both the x- and y-axis
directions, and to detect head size (width and height), on average, to within one and two pixels of
the measured head width and height, respectively. Our head movement tracking system tracks
head rotations, on average, to within 1.4° of the measured angles.. Our tracker is capable of
processing up to eight captured images per second. === Science, Faculty of === Computer Science, Department of === Graduate
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