Title

Mobile visual search via hievarchical sparse coding

Publication Type

Conference Proceeding Article

Publication Date

7-2014

Abstract

Mobile visual search is attracting much research attention recently. Existing works focus on addressing the limited capacity of wireless channel yet overlook its instability, thus is not adaptive to the change of channel capacity. In this paper, a novel image retrieval algorithm that is scalable to various channel condition is proposed. The proposed algorithm contains three contributions: (1) to achieve instant retrieval under various channel capacity, we adjust transmission load by sparseness instead of codebook size; (2) we introduce hierarchical sparse coding into our retrieval workflow, where original codebook is transformed into a tree-structured dictionary which implies elements' priority; (3) we propose transmission priority ranking schemes that is adaptive to specific query. Experiment results show that the proposed algorithm outperforms BoW and Lasso based algorithm under different parameter settings. Retrieval results under different channel limitation validate the scalability of our method.

Discipline

Databases and Information Systems

Research Areas

Data Management and Analytics

Publication

IEEE International Conference on Multimedia and Expo (ICME 2014): 14-18 July 2014, Chengdu: Proceedings

First Page

1

Last Page

6

ISBN

9781479947607

Identifier

10.1109/ICME.2014.6890294

Publisher

IEEE

City or Country

Piscataway, NJ

Additional URL

http://dx.doi.org/10.1109/ICME.2014.6890294