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JACIII Vol.3 No.1 pp. 56-65
doi: 10.20965/jaciii.1999.p0056
(1999)

Paper:

Linguistic Expression Generation Model of Subjective Content in a Picture

Mitsuru Iwata* and Takehisa Onisawa**

*Doctoral Program in Engineering, University of Tsukuba

**Institute of Engineering Mechanics & Center for Tsukuba Advanced Research Alliance (TARA), University of Tsukuba
1-1-1 Tennodai, Tsukuba, 305-8573, Japan

Received:
July 22, 1998
Accepted:
September 18, 1998
Published:
February 20, 1999
Keywords:
story generation, subjective information, neural network, fuzzy inference, case-based reasoning
Abstract

As a first step in modeling human intelligent information processing, we describe a model that extracts subjective content from a given picture using objective picture information and generates linguistic expressions. In this model, subjective content is emotions of a human object, the relationship between two objects, and object behavior in a picture. Objective picture information includes object location, size, direction, etc. Model reasoning involves soft computing techniques such as neural networks, fuzzy reasoning, and case-based reasoning. Neural networks recognize human emotions from facial expressions. Fuzzy reasoning infers the degree to which an organism discerns other objects. Case-based reasoning draws object behavior from a picture. This subjective content extracted from a picture is expressed by linguistic expressions using fuzzy sets. A simulation example shows that this model extracts subjective content about an object in a picture. The model’s effectiveness was confirmed by two types of experiment.

Cite this article as:
Mitsuru Iwata and Takehisa Onisawa, “Linguistic Expression Generation Model of Subjective Content in a Picture,” J. Adv. Comput. Intell. Intell. Inform., Vol.3, No.1, pp. 56-65, 1999.
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Last updated on Dec. 02, 2021