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2.3. Motion Editing
Figure 2.10: Biomechanical system for natural head-neck movements [Lee and Terzopoulos,
2006].
plants [Kulpa et al., 2005]. This method allows them to share a motion between several characters
having different morphologies. They equally adapted a hierarchical Cyclic Coordinate
Descent (CCD) algorithm taking advantage of this representation to deal with spacetime
constraints for the characters. All these analytic methods are dedicated to the positioning of
end-effectors. In this thesis, we are interested in controlling the final orientation of the eyes,
head, and spinal joints over time instead.
Somewhat between models of human vision and motion editing, Lee et al. proposed
an eye movement model which they based on empirical models of saccades and statistical
models of eye-tracking data [Lee et al., 2002c]. Their approach consisted in using the spatiotemporal
trajectories of saccadic eye movements to synthesize the kinematic characteristics
of the eye. They first analyzed a sequence of eye-tracking images in order to extract the
spatio-temporal trajectories of the eye. With this, they derived two statistical models of the
saccades which occur, for talking mode and listening mode. Their model reflects saccade
magnitude, direction, duration, velocity, and inter-saccadic intervals. Figure 2.9 illustrates
their method with a couple of examples.
Lee and Terzopoulos proposed a head-neck model based on biomechanics which emulates
the anatomy of the human neck [Lee and Terzopoulos, 2006]. They also presented a
neuromuscular control model in order to animate the head and the neck. Their method allows
the simulation of head pose and movement, but also the stiffness of the head-neck multibody
system, as shown in Figure 2.10. Even though such a method gives stunning results, its
computational times are prohibitive for crowd animation.
Instead, we present an extremely fast analytic dedicated gaze IK solver to handle the
orientation of both eyes, the head, and the spine. Given a pre-existing animation, our solver
computes the displacement maps for characters to satisfy predefined gaze constraints. These
displacements are smoothly propagated onto the original motion to ensure that the final results
are continuous. Our method deals with dynamic constraints and manages both the
spatial and temporal distribution of the displacements.
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