Efficient Cross-modal Retrieval Using Social Tag Information Towards Mobile Applications
文献类型：会议论文
| 作者 | Jianfeng He; Qingming Huang; Weigang Zhang; Qiang Qu; Shuhui Wang |
| 出版日期 | 2017 |
| 会议日期 | 2017 |
| 会议地点 | 德国慕尼黑 |
| 英文摘要 | With the prevalence of mobile devices, millions of multimedia data represented as a combination of visual, aural and textual modalities, is produced every second. To facilitate better information retrieval on mobile devices, it becomes imperative to develop efficient models to retrieve heterogeneous content modalities using a specific query input, e.g., text-to-image or image-to-text retrieval. Unfortunately, previous works address the problem without considering the hardware constraints of the mobile devices. In this paper, we propose a novel method named Trigonal Partial Least Squares (TPLS) for the task of cross-modal retrieval on mobile devices. Specifically, TPLS works under the hardware constrains of mobile devices, i.e., limited memory size and no GPU acceleration. To take advantage of users’ tags for model training, we take the label information provided by the users as the third modality. Then, any two modalities of texts, images and labels are used to build a Kernel PLS model. As a result, TPLS is a joint model of three Kernel PLS models, and a constraint to narrow the distance between label spaces of images and texts is proposed. To efficiently learn the model, we use stochastic parallel gradient descent (SGD) to accelerate the learning speed with reduced memory consumption. To show the effectiveness of TPLS, the experiments are conducted on popular cross-modal retrieval benchmark datasets, and competitive results have been obtained. |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/11930]  |
| 专题 | 深圳先进技术研究院_其他 |
| 作者单位 | 2017 |
| 推荐引用方式 GB/T 7714 | Jianfeng He,Qingming Huang,Weigang Zhang,et al. Efficient Cross-modal Retrieval Using Social Tag Information Towards Mobile Applications[C]. 见:. 德国慕尼黑. 2017. |
入库方式： OAI收割
来源：深圳先进技术研究院
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