Difference: TrajOpt (6 vs. 7)

Revision 72006-03-20 - batty

Line: 1 to 1

META TOPICPARENT	name="CPSC526ComputerAnimation"

-- MichielVanDePanne - 27 Feb 2006

Line: 21 to 21

(Spacetime constraints) A very good paper in my view, which is I believe being used later on in different works. The main problem is that they refer to motion data but their example is using particles which have significantly less degrees of freedom. So the challenge is to apply it to motion capture data (which is illustrated in the other paper). -- Hagit Schechter

Added:

>
>

How does it scale, if we have to deal with this crazy high dimensional optimization problem? especially for more complex systems like human characters... Then again, I wonder what you could pull off today, given that this was published nearly 20 years ago. It seems impressive for the time, and it's obviously an interesting approach to the problem of partially automating motion of characters. --Christopher Batty

Paper Two (Synthesizing Human Motion)

Line: 35 to 38

(Synthesizing physically realistic human motion) The paper combines different works in the field and synthesizes into one that makes a lot of sense to me. The first comment that I have is related to selecting the basis motions, currently done by the user. My question is, have there been related works to compute the best basis motions, opposed to having the user select them? The second comment is related to their statement that in general they got less reliable motion when running the optimization in higher dimensions. They do not provide a good explanation for that (after all – that is un-intuitive), and I wonder if someone can come up with an explanation for that. -- Hagit Schechter

Added:

>
>

This seems to be one approach to overcoming scalability difficulties of original space-time constraints paper. It's frustrating that the method is fairly slow AND there is no guarantee of convergence for motions that diverge somewhat from the training data, but it is nifty that it can sometimes generalize beyond the input data. As an animation physics guy I like the idea of combining equations of motion with models from motion capture as they do here The claim that the lower dimensional representation increases the naturalness of the optimized result is intriguing. I wonder if there's an intuitive explanation of why this might be the case, eg. The low dimensional model encompasses the natural motion defined in the database, but by optimizing with a larger number of dimensions it allows more flexibility for the mathematical/physics constraint optimization to take over causing greater divergence from "natural" looking motion. -Christopher Batty

View topic | History: r8 < r7 < r6 < r5 | More topic actions...