Mobile visual search via hievarchical sparse coding
Conference Proceeding Article
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.
Databases and Information Systems
Data Management and Analytics
IEEE International Conference on Multimedia and Expo (ICME 2014): 14-18 July 2014, Chengdu: Proceedings
City or Country
Yang, Xiyu; Liu, Lianli; Qian, Xueming; Mei, Tao; SHEN, Jialie; and QI, Tian.
Mobile visual search via hievarchical sparse coding. (2014). IEEE International Conference on Multimedia and Expo (ICME 2014): 14-18 July 2014, Chengdu: Proceedings. 1-6. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/2498