Efficient Region of Visual Interests Search for Geo-multimedia Data

TL;DR

This paper introduces a new spatial query called RoVIQ for retrieving geo-tagged multimedia data, and proposes a quadtree-based inverted visual index to improve search efficiency, validated by experiments on real datasets.

Contribution

It defines the novel RoVIQ problem and develops a quadtree-based inverted visual index to enhance spatial multimedia retrieval performance.

Findings

Our method outperforms existing techniques in retrieval speed.

The proposed index improves search accuracy and efficiency.

Experimental results validate the effectiveness of the approach.

Abstract

With the proliferation of online social networking services and mobile smart devices equipped with mobile communications module and position sensor module, massive amount of multimedia data has been collected, stored and shared. This trend has put forward higher request on massive multimedia data retrieval. In this paper, we investigate a novel spatial query named region of visual interests query (RoVIQ), which aims to search users containing geographical information and visual words. Three baseline methods are presented to introduce how to exploit existing techniques to address this problem. Then we propose the definition of this query and related notions at the first time. To improve the performance of query, we propose a novel spatial indexing structure called quadtree based inverted visual index which is a combination of quadtree, inverted index and visual words. Based on it, we design a efficient search algorithm named region of visual interests search to support RoVIQ. Experimental evaluations on real geo-image datasets demonstrate that our solution outperforms state-of-the-art method.