DocumentCode
285203
Title
Figure recognition with intentional observation
Author
Sakaguchi, Yutaka ; Nakano, Kaoru
Author_Institution
Dept. of Math. Eng. & Inf. Phys., Tokyo Univ., Japan
Volume
3
fYear
1992
fDate
7-11 Jun 1992
Firstpage
792
Abstract
When perceiving an object humans do not receive stimuli passively, but observe the object actively to obtain useful information for recognizing it. A neural network model which realizes such active perception by utilizing neural dynamics is proposed. The model consists of a sensory unit, a representation field, and recognition units. The model sequentially collects local information of the presented figure, gradually constructs its internal image, and recognizes it based on the constructed internal image. An intentional observation mechanism was constructed by which the model can selectively observe informative parts of the figure for constructing the internal image. Several computer simulation results are described. The model is discussed from the viewpoint of Bayesian inference and information theory
Keywords
Bayes methods; inference mechanisms; information theory; neural nets; visual perception; Bayesian inference; active perception; figure recognition; information theory; intentional observation; neural dynamics; neural network model; recognition units; representation field; sensory unit; Bayesian methods; Biological systems; Computer simulation; Computer vision; Humans; Neural networks; Pattern recognition; Physics; Psychology; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location
Baltimore, MD
Print_ISBN
0-7803-0559-0
Type
conf
DOI
10.1109/IJCNN.1992.227055
Filename
227055
Link To Document