Monthly Archives: January 2008

Levenberg-Marquardt algorithm

In mathematics and computing, the Levenberg-Marquardt algorithm (or LMA) provides a numerical solution to the problem of minimizing a function, generally nonlinear, over a space of parameters of the function. These minimization problems arise especially in least squares curve fitting and nonlinear programming.
The LMA interpolates between the Gauss-Newton algorithm (GNA) and the method of gradient descent. The LMA is more robust than the GNA, which means that in many cases it finds a solution even if it starts very far off the final minimum. On the other hand, for well-behaved functions and reasonable starting parameters, the LMA tends to be a bit slower than the GNA.
The LMA is a very popular curve-fitting algorithm; most software with generic curve-fitting capabilities provides an implementation of it.



structure from motion

查了一下资料,发现SfM这个问题已经在Multiple view geometry这本书中讲的比较清楚了。SfM的最后一步,bundle adjustment网上也有现成的程序,。剩下得就是好好研究这些资料了。

今天在查SfM的时候想起来了Photo tourism这篇paper,就又看了一下。发现这个paper已经被微软做成产品了,photosynth,很cool。

Structure and Motion的matlab code