Automatic Semantic Annotation for Image Retrieval Based on Multiple Kernel Learning

DOI

10.2991/lemcs-14.2014.148How to use a DOI?

Keywords

semantic annotation; spatial pyramid (SP); histogram intersection kernel (HIK); Radical Basic Kernel function; multiple kernel learning (MKL).

Abstract

The image low level features have a gap with the high level semantic feature which human understand, the researches begin to focus on automatic semantic annotation image retrieval rather than on content image retrieval. The previous methods mostly base on single kernel learning, which has some limitations, which is no effective feature information processing. In this article, an automatic image annotation framework is proposed based on Radial Basic Kernel function combining Spatial Pyramid and Histogram Intersection Kernels. This framework utilizes multiple kernel learning, the k-mean clusters the training images to dictionary. The feature parameters are optimized Spatial Pyramid and Histogram Intersection Kernel. Then radical basic kernel function trains the data and predicts the labels of the images. Spatial Pyramid, reflecting features of location information, is more exact than Bag of Word. Experimental results demonstrated that the proposed framework effectively improves the performance of image annotation and outperform state-of- the-art on the multiple databases.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Alin Hou
AU  - Chongjin Wang
AU  - Junliang Guo
AU  - Liang Wu
AU  - Fei Li
PY  - 2014/05
DA  - 2014/05
TI  - Automatic Semantic Annotation for Image Retrieval Based on Multiple Kernel Learning
BT  - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science
PB  - Atlantis Press
SP  - 649
EP  - 653
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-14.2014.148
DO  - 10.2991/lemcs-14.2014.148
ID  - Hou2014/05
ER  -