DocumentCode
295894
Title
The EM algorithm for multiple object recognition
Author
Akaho, Shotaro
Author_Institution
Electrotech. Lab., Ibaraki, Japan
Volume
5
fYear
1995
fDate
Nov/Dec 1995
Firstpage
2426
Abstract
Proposes a mixture model that can be applied to the recognition of multiple objects in an image plane. The model consists of any shape of modules; each module is a probability density function of data points with scale and shift parameters, and the modules are combined with weight probabilities. The author presents the EM (Expectation-Maximization) algorithm to estimate those parameters. The author also modifies the algorithm in the case that data points are restricted in an attention window
Keywords
normal distribution; object recognition; probability; EM algorithm; attention window; expectation-maximization algorithm; image plane; multiple object recognition; probability density function; weight probabilities; Concrete; Image recognition; Laboratories; Maximum likelihood estimation; Object recognition; Parameter estimation; Probability density function; Probability distribution; Random variables; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.487742
Filename
487742
Link To Document