Content deleted Content added
added link |
m clean up, typo(s) fixed: However → However, (2) using AWB |
||
Line 45:
== Non-maximum suppression ==
"Since the segment test does not compute a corner response function, [[non-maximum suppression]] could not applied directly to the resulting features." However, if N is fixed, for each pixel p the corner strength is defined as the maximum value of t that makes p a corner. Two approaches therefore could be used:
*A [[binary search algorithm]] could be applied to find the biggest t for which p is still a corner. So each time a different t is set for the decision tree algorithm. When it manages to find the biggest t, that t could be regarded as the corner strength.
*Another approach is an iteration scheme, where each time t is increased to the smallest value of which pass the test.
== FAST-ER: Enhanced repeatability ==
FAST-ER detector is an improvement of the FAST detector using a [[metaheuristic]] algorithm, in this case [[simulated annealing]]. So that after the optimization, the structure of the decision tree would be optimized and suitable for points with high repeatability. However, since [[simulated annealing]] is a metaheurisic algorithm, each time the algorithm would generate a different optimized decision tree. So it is better to take efficiently large amount of iterations to find a solution that is close to the real optimal. According to Rosten, it takes about 200 hours on a Pentium 4 at 3 GHz which is 100 repeats of 100,000 iterations to optimize the FAST detector.
== Comparison with other detectors ==
Line 165:
<!--- Categories --->
[[Category:Feature detection (computer vision)]]
| |||