Active Vision through Invariant Representations and Saccade Movements

 
 
 
 

Active Vision through Invariant Representations and Saccade Movements

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Title: Active Vision through Invariant Representations and Saccade Movements
Author: Li, Yue
Description: This thesis presents an innovative approach to pattern recognition, by using self-organized, invariant representations integrating continuous observation and saccade movements. This biologically motivated approach can achieve visual perception through a retina like sampling of high resolution images with lower resolution artificial retina. The neural network uses hierarchical feedback structures to build object representations, self-organizes invariant transformations, while iterates on the images received from the retina model. The network identifies the whole image by using winner-take-all scheme through temporal association of sufficiently accurate saccades. By using our invariance building scheme, the network can identify different views of the same object.
Permanent Link: http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1149389174
http://hdl.handle.net/2374.OX/13582
Date: 2006

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