1089 
4. CONCLUSIONS 
In this paper, a new feature extraction method for object 
recognition tasks based on incremental update of the non- 
Gaussian independent vectors has been used. This method 
concentrates on a challenging issue of computing dominating 
non-Gaussian vectors from an incrementally arriving high 
dimensional data stream without computing the corresponding 
covariance matrix and without knowing the data in advance, and 
the results are to be compared with PCA and ICA. Three 
experiments were performed with different pose and non 
Gaussian vectors. 
The images of the COIL database have been originally used by 
many people for testing the appearance-based recognition system, 
based on the notion of parametric non Gaussian space Our results 
seem to compare favorably with respect to the results reported in 
[1][2], Note that IPCA not only allows for the construction of 
training images of much smaller size, but also can identify the 
object pose. Experiment results in appearance-based 3D Object 
Recognition confirm IPCA offer better recognition rates. 
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