Rabbit, toad, and the Moon: Can machine categorize them into one class?

TL;DR

This paper explores a novel approach to classifying objects like rabbits, toads, and the Moon into one category based on their basal dynamic patterns, emphasizing cyclic behavior over static features.

Contribution

It introduces the concept of using basal dynamic patterns and image schemas for object classification, linking cultural symbolism with machine learning.

Findings

Cyclic appearance and disappearance serve as key features for classification.

Static shape and time scale are not essential for categorization.

Preliminary discussion suggests potential for cognitive and computational applications.

Abstract

Recent machine learning algorithms such as neural networks can classify objects and actions in video frames with high accuracy. Here, I discuss a classification of objects based on basal dynamic patterns referencing one tradition, the link between rabbit, toad, and the Moon, which can be seen in several cultures. In order for them to be classified into one class, a basic pattern of behavior (cyclic appearance and disappearance) works as a feature point. A static character such as the shape and time scale of the behavior are not essential for this classification. In cognitive semantics, image schemas are introduced to describe basal patterns of events. If learning of these image schemas is attained, a machine may be able to categorize rabbit, toad, and the Moon as the same class. For learning, video frames that show boundary boxes or segmentation may be helpful. Although this discussion is preliminary and many tasks remain to be solved, the classification based on basal behaviors can be an important topic for cognitive processes and computer science.