training image from google, testing on Caltech dataset
unsupervised learning algorithm
pLSA
no spatial information
ABS-pLSA
latent variable x (grid centroid coordinate)
grid methodology, still translation and scaling variant
TSI-pLSA
latent variable c:(centroid, xscale, yscale)
1. apply to pLSA
2. fit a mixture of Gaussian with k=(1, 2, ...K) components to the location of the region, weighted by p(w|z)
3.
unsupervised learning algorithm
pLSA
no spatial information
ABS-pLSA
latent variable x (grid centroid coordinate)
grid methodology, still translation and scaling variant
TSI-pLSA
latent variable c:(centroid, xscale, yscale)
1. apply to pLSA
2. fit a mixture of Gaussian with k=(1, 2, ...K) components to the location of the region, weighted by p(w|z)
3.