Difference: TrajOpt (5 vs. 6)

Revision 62006-03-20 - HagitSchechter

Line: 1 to 1

META TOPICPARENT	name="CPSC526ComputerAnimation"

-- MichielVanDePanne - 27 Feb 2006

Line: 18 to 18

First of all, this paper is a fun read just because of its age. I was 6 1/2 years old when this was written. I love the mention of "acceleration by array processors" and how systems with less than 1000 variables are solved in "under 10 minutes". So old! Another nice property regarding the generation of this paper is its wording. Perhaps it is due to the novelty of SIGGRAPH as a conference at the time, but this paper reads more like a good textbook than a conference paper (i.e., it provides a nice introductory example, works through the details and really assumes little prior knowledge). Anyways, while reading the paper, the two questions that were outstanding in my head were "does this apply to human figures with more than four DOF?" and "Yes, optimization is cool, but what function do you minimize and what constraints do you put in?". Indeed, both of these are still (see my comments on the next paper) open problems and are areas for active research. The jumping Luxo result is nice, which shows immediate application of the technique to motions of low dimensional figures. One final note is that I quite enjoy the fact that they used LISP to develop their math compiler and runtime system. -- KenRose

Added:

>
>

(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

Paper Two (Synthesizing Human Motion)

Another paper. Please add your comments below.

Line: 29 to 33

I regard this paper an excellent sequel to the Spacetime Constraints paper. The background section nicely explains other work in the area of dimensionality reduction and use of optimization for synthesizing motion. Sadly, the state of the art still seems to be "high dimensions are hard" due to a variety of reasons (contact forces, objective functions with torque, system size, etc.). I like their objective function since it really only depends on three parameters (w_T, w_A and w_P), which is simple enough for a human to manipulate. While reading the paper, I thought that it would be nice if the user didn't have to specify which motions from the database that are similar to the desired motion. Indeed, the authors also pointed this out in the Discussion section at the end. -- KenRose

Added:

>
>

(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

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