DDT version 6
Post date: Sep 2, 2011 6:05:54 PM
Basically, DDT is a new name for ITSBN. In this post we illustrate the performance of DDT version 6 with the following parameters:
- There are totally 6 levels (root included), whose number of superpixels in each level are approximately 1, 20, 60, 80, 200 and 1500 respectively. Note that the leaf level of DDT version 6 are pixel-level node 1% randomly sampled from pixels in each superpixel. This is the main focus of the version 6.
- Some levels are tied together for inference stability:
- tie_level_table = [1 1
- 2 2
- 3 3
- 4 4
- 5 4
- 6 4];
- Each tied level has its own number of classes and the DDT parameters
- tie_parameter_table = [1 7 1
- 2 7 1
- 3 5 1
- 4 3 1];
- Number of maximum iterations is 15
There are several questions I try to answer in this experiment
- Quality of DDTv6 vs superGMM
- We found that DDTv6 performs competitively to superGMM with the same initialization.
- Does the quality of segmentation depend on the log-likelihood?
- The segmentation quality strictly depends on the log-likelihood in the very beginning of the iteration, say 1-5, however, after iteration 10, the log-likelihood still keeps increasing whereas the segmentation seems to remain the same. So, I think setting the maximum number of iterations to 10 is sufficient to get high-quality segmentation.
- What is the optimal number of iteration?
- Around 10
- Run-time vs # of nodes
- Please refer to the end of this post.
Sample results are shown in the slides below