Title :
Classification of individually pleasant images based on neural networks with the bag of features
Author_Institution :
Inst. of Technol. & Sci., Univ. of Tokushima, Tokushima, Japan
Abstract :
It is important to determine the correct semantic categories for the classification of photographic scenes. In particular, it is difficult to categorize emotional pictures, including individually pleasant or unpleasant contents. Therefore, the method of searching for individually emotional information from various pictures was investigated using neural networks with the bag of features scheme. The neural network classifier for emotional pictures performed a partially accurate estimation; however, there were some cases in which the bag of features scheme based on local features mistakenly selected similar images in a different semantic category. Further robust searching methods for individually emotional categorization must be considered.
Keywords :
image classification; neural nets; photography; bag of feature scheme; emotional information; emotional picture category; individually pleasant image classification; neural network; neural network classifier; partially accurate estimation; photographic scene classification; robust searching method; semantic category; Accuracy; Artificial neural networks; Feature extraction; Object recognition; Semantics; Visualization; bag of features; emotional pictures; neural networks; object recognition;
Conference_Titel :
Orange Technologies (ICOT), 2013 International Conference on
Conference_Location :
Tainan
Print_ISBN :
978-1-4673-5934-4
DOI :
10.1109/ICOT.2013.6521215