I am using lsqnonlin in MATLAB to align a rigid skeleton model to raw joint center data recorded from a device that does not necessarily yield a rigid skeleton. Therefore, my objective function to be minimized is the distance between model joint locations and raw data joint locations.
My algorithm does a pretty good job (red is the rigid model and blue is the raw data):
except for some select frames where my skeleton is off:
I am interested in examining the solution process graphically so that I can visualize what lsqnonlin is trying to do for every frame. Ideally, I would output a History but this seems to be only available for other solvers.
For lsqnonlin it seems that I need to specify a plotting function for the PlotFcn option in optimoptions. I have extracted from the optimation Toolbox the function optimplotx.m which displays a bar graph of the state variables during the iteration process as lsqnonlin converges. My plan is to tweak this function to reproduce the plot for the red skeleton previously displayed.
My problem is that the quantity to be optimized is not the joint locations themselves, but joint angles. I have another function which does forward kinematics and gives me joint positions from joint angles. I would like to pass model parameters into optimplotx.m so that I may call my forward kinematics function and get the plot done but I am unsure how to do that.
These are the inputs to optimplotx.m:
It seems that somewhere deep in the Optimization Toolbox, MATLAB expects these inputs, and they are not to be changed. It is required that I call @optimplotx anonymously anyway, without passing in arguments. It seems that the only way I might be able to get around this is to make my model parameters global in both my main file and optimplotx. Is there any way around this?