标题: PROGRESSIVE TRANSITIONS USING BODY PART MOTION GRAPHS [打印本页] 作者: 彬彬 时间: 2011-12-28 09:09 标题: PROGRESSIVE TRANSITIONS USING BODY PART MOTION GRAPHS Abstract
In this work we describe a preliminary method for progressive transitions
in human locomotions. To achieve this, motion graphs have
been used to synthesize body part transitions and every part has
been synchronized with the other parts using time scaling. Lastly,
we have compared transition costs and graph connectiviy of our
method to standard motion graphs. The results are promising to allow
better smoothness and response in motion clips concatenation.
1 Introduction
Automatic concatenation from motion capture clips in order to create
a larger stream of movements has been a wide research area in
3D character animation. In 2002, motion graph appears in various
works such as [Kovar et al. 2002][Lee et al. 2002]. Motion graph
consists in the assembling of motion capture data in a graph connecting
similar frames that are below a similarity pose threshold.
Distance metrics are computed to know this similarity. Common
distance metrics compute some function to compare frames, taking
into account full body posture. To refine this comparison, weights
are assigned to joints giving more or less importance to them. These
weights are of great importance and can change the transition points
between motion clips [Wang and Bodenheimer 2008]. Finally, motions
are connected satisfying user input.
Searching similar full body postures, as in standard motion graphs
(SMG), can sometimes be tricky. Two frames having the same posture,
except for some joints, could overcome the threshold similarity
even though the whole body is similar enough. Not being
able to find similar positions affects graph connectivity and reduces
the possibility of transitions between different kind of motions. In
Fig. 1 there are some transition matrices (distance between frames)
clustering joints in body parts (BP). As we can see, good transition
points (dark zones) are located in close positions of each map, but
not exactly in the same place. These differences show that transitioning
all joints at same time (in a SMG way) could be not optimal.
Therefore, we propose to divide the body into body parts and transition
each part independently. Some other works use similar body
part segmentation [Jang et al. 2008] [Ng et al. 2010], but they focus
on attaching body part motions from different motions in order to
enlarge a motion capture database. However, this is not our goal,
we are focused on searching good transition points for every body
part and generating their specific transitions. The main problem
with this approach is synchronization. Locomotions are the sum of
body part movements with a specific synchrony and cadence. We
deal with this issue searching transitions for each part of the body in
a time window, and then we edit submotions to ensure synchronization
and coherence. This process will be properly described in next
section. We have called our method progressive transitions using
body part motion graphs (BPMG’s).作者: 彬彬 时间: 2012-1-13 14:09