We propose a method to find candidate 2D articulated model configurations by searching for locally optimal configurations
under a weak but computationally manageable fitness function. This is accomplished by first parameterizing a tree structure
by its joints. Candidate configurations can then efficiently and exhaustively be assembled in a bottom-up manner. Working
from the leaves of the tree to its root, we maintain a list of locally optimal, yet sufficiently distinct candidate configurations
for the body pose.
We then adapt this algorithm for use on a sequence of images by considering configurations that are either near their position
in the previous frame or overlap areas of interest in subsequent frames. This way, the number of partial configurations generated
and evaluated significantly reduces while both smooth and abrupt motions can be accommodated. This approach is validated on
test and standard datasets.