Image Location Estimation by Salient Region Matching

Abstract

Nowadays, locations of images have been widely used in many application scenarios for large geo-tagged image corpora. As to images which are not geographically tagged, we estimate their locations with the help of the large geo-tagged image set by content-based image retrieval. In this paper, we exploit spatial information of useful visual words to improve image location estimation (or content-based image retrieval performances). We proposed to generate visual word groups by mean-shift clustering. To improve the retrieval performance, spatial constraint is utilized to code the relative position of visual words. We proposed to generate a position descriptor for each visual word and build fast indexing structure for visual word groups. Experiments show the effectiveness of our proposed approach.

Travel Guide- A Personalization Of Travel Package Recommendation System

“…user can transfer knowledge across regions to recommend for an user in a new region [2] The new solution is simple and fast the given solution improves accuracy from 48% for a traditional BOW solution to 60%, while maintaining the same processing time [3] Our experimental results demonstrate the significance it would be interesting to investigate the recommendation effect of content information compared to other information, such as spatial, temporal, or social information [4] they focus on the problem of time-aware POI recommendation, which considers the temporal influence in user activities they for POI recommendation on the GTAG. or future it would be interesting to apply the proposed framework to time-aware recommendation in other tasks [5] Content based filtering is approach used for generating recommendation They present a salient feature mining based approach to improve the performance of GPS location estimation Experiments demonstrate that our method out performs the classical and state-of-theart method for image GPS estimation [6] …”

Travel Recommendation Based on Data From Social Media

“…We additionally purpose out the variations between our work and existing works. GPS trajectory [5], check-in knowledge [4], [6], [7] geo-tags [2], [3], [8], [9], [10] and blogs (travelogues) are four main social media used in recommendation. User generated travelogues provide wealthy data.…”

“…For example, it may still not be a decent recommendation if all the POIs suggested for in the future ar in four corners of the town, even though the user is also curious about all the individual POIs. Existing studies on travel recommendation mining famous travel POIs and routes ar in the main from four sorts of huge social media, GPS trajectory [5], check-in information [4], [6], [7] geo-tags [2], [3], [8], [9], [10] and blogs (travelogues). However, general travel route planning cannot well meet users" personal necessities.…”

Personalized Portable Travelogue Guide on Multi-Source Big Social Media

“…Yisi Zhao [8] explains about estimating the locations of images which has been received over a attention. In this paper, visual word group base approach is used.…”