AUTOMATICALLY COMPUTING EMOTIONS AROUSED FROM IMAGES THROUGH SHAPE MODELING

摘要

Shape features in natural images influence emotions aroused in human beings. An in-depth statistical analysis helps to understand the relationship between shapes and emotions. Through experimental results on the International Affective Picture System (IAPS) dataset, evidence is presented as to the significance of roundness-angularity and simplicity-complexity on predicting emotional content in images. Shape features are combined with other state-of-the-art features to show a gain in prediction and classification accuracy. Emotions are modeled from a dimensional perspective in order to predict valence and arousal ratings, which have advantages over modeling the traditional discrete emotional categories. Images are distinguished vis-a-vis strong emotional content from emotionally neutral images with high accuracy. All of the methods and steps disclosed herein are implemented on a programmed digital computer, which may be a stand-alone machine or integrated into another piece of equipment such as a digital still or video camera including, in all embodiments, portable devices such as smart phones.

主权项

1. A system for analyzing the emotional content of an image, comprising the steps of:
a programmed computer having an input for receiving at least one digital image, wherein the computer is programmed to perform the following functions automatically:
(a) extract visual information from the image;(b) model shape features in the image, and(c) compute the emotional content of the image based upon the extracted visual features and modeled shape features; and an output device in communication with the programmed computer enabling a user to receive the computed emotional content of the image.