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Tag-based semantic features for scene image classification

Version 2 2024-06-05, 11:55
Version 1 2020-01-09, 08:34
conference contribution
posted on 2024-06-05, 11:55 authored by C Sitaula, Yong XiangYong Xiang, A Basnet, Sunil AryalSunil Aryal, X Lu
The existing image feature extraction methods are primarily based on the content and structure information of images, and rarely consider the contextual semantic information. Regarding some types of images such as scenes and objects, the annotations and descriptions of them available on the web may provide reliable contextual semantic information for feature extraction. In this paper, we introduce novel semantic features of an image based on the annotations and descriptions of its similar images available on the web. Specifically, we propose a new method which consists of two consecutive steps to extract our semantic features. For each image in the training set, we initially search the top k most similar images from the internet and extract their annotations/descriptions (e.g., tags or keywords). The annotation information is employed to design a filter bank for each image category and generate filter words (codebook). Finally, each image is represented by the histogram of the occurrences of filter words in all categories. We evaluate the performance of the proposed features in scene image classification on three commonly-used scene image datasets (i.e., MIT-67, Scene15 and Event8). Our method typically produces a lower feature dimension than existing feature extraction methods. Experimental results show that the proposed features generate better classification accuracies than vision based and tag based features, and comparable results to deep learning based features.

History

Volume

11955

Pagination

90-102

Location

Sydney, N.S.W.

Start date

2019-12-12

End date

2019-12-15

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783030367176

Language

eng

Publication classification

E1 Full written paper - refereed

Editor/Contributor(s)

Gedeon T, Wong K, Lee M

Title of proceedings

ICONIP 2019 : Proceedings of the 26th International Conference on Neural Information Processing of the Asia-Pacific Neural Network Society 2019

Event

Asia-Pacific Neural Network Society. International Conference (26th : 2019 : Sydney, N.S.W.)

Publisher

Springer

Place of publication

Cham, Switzerland

Series

Asia-Pacific Neural Network Society International Conference

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