iFRAME (inhomogeneous Filters Random Field And Maximum Entropy)

Experiment 2: Wavelet Selection by Generative Boosting

data

Learning sequences by generative boosting are displayed. The first row shows the evolution of the sketch templates. Each selected Gabor wavelet is illustrated by a bar, and each DoG by a circle. The template is the superposition of Gabor wavelets of 4 scales and DoG wavelets of 2 scales, where smaller scales appear darker. The second row shows the synthesized images that are generated when the number of selected wavelets n = 1, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, and 700.


Case 1: Hummingbird


Case 2: Wolf


Case 3: Bike


Case 4: Flamingo


Case 5: Falcon


Typical parameters:
image size is 100x100. The number of basis functions is 700. The allowed range of perturbation in location is 2 pixels. The allowed range of perturbation in rotation is pi/16. GaborScaleList=[ 1.4, 1,0.7,0.5]. DoGScaleList =[18.90,13.36]. interval=3. 6x6 chains.
threshold_corrBB = 0; lower_bound_rand = 0.001; upper_bound_rand = 0.999;c_val_list=-25:2:25.