Combining multiple estimates

[Ruggero Milanese]

Hello,

I am interested in computing the trajectory and the velocity parameters 
of objects moving in the camera field of view, combining classical computer 
vision and neural network algorithms. I have several measures/estimates of 
the motion parameters, extracted through different methods. 
I am interested in combining these estimates in order to obtain a 
"combined-estimate" which is closer to the "real values". 

So far, I have found the following papers that seem relevant to this problem:

	- "Combining estimators using non-constant weighting functions", 
	by V. Tresp and M. Taniguchi, Advances in Neural Information 
	Processing Systems 7, MIT Press, 1995. 

	- "Multitarget-Multisensor Tracking: Advanced Applications", editor
	Bar-Shalom, Artech House, 1990. 

	- "Optimal linear combination of neural networks", PhD. Thesis 
	Sh. Hashem, 1993. 

Could anyone please give me any other pointers or suggest alternative
approaches that possibly use non-constant weighting functions?

Please send replies to:

  Sylvia Gil                             Dept. of Computer Science
  E-mail: gil at cui.unige.ch               University of Geneva
  Phone:  +41 (22) 705-7628              24, rue du General Dufour
  Fax:    +41 (22) 705-7780              1211 Geneva 4 
  http://cuiwww.unige.ch                 Switzerland

Thank you a lot.

-Ruggero Milanese
 University of Geneva, Switzerland
 milanese at cui.unige.ch