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Contribution: The authors use physics-based dynamics to develop natural parameterizations of human motion. Physical interactions with the environment are also possible. The scheme generalizes to different speeds, masses, etc. of walking models. By modeling the underlying dynamics, more realistic motions and accurate tracking are achieved in comparison to modeling based solely on kinematics.
Evaluation: The authors evaluate their system quite vigorously. Comparison of the performance of the system to mocap data is much appreciated. A statistical analysis of how well the model generalizes to variability such as changes in speed, introducing occlusions and turning. The use of test data (from an independent project, HumanEva) not contained in the training set is essential and, although results are not exceptional, gives a much better gauge the generalization capabilities of the system.
Reproducibility: Though details in terms of formulas and theory of the underlying system are well presented, there seems to be a lack in practical advise on how to reimplement their solution in software. The authors make up for this deficiency by publishing the matlab source code of the project.
Improvements: Being a journal article, the work is high quality. If I had to complain about anything, it would be that complexity of the system is quite high. How they managed to squeeze a discussion of particle filters on top of all that is beyond me.
-- DanielTroniak - 02 Dec 2011 |