Can Geotags Help Image Recognition?

Yaegashi, Keita; Yanai, Keiji

doi:10.1007/978-3-540-92957-4_32

Cited by 10 publications

(3 citation statements)

References 9 publications

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“…It is a just 2-dimensional vector. To convert a 2-d vector into richer representation, Luo et al 83) and Yaegashi et al 137) converted geotags into visual information from the sky using aerial images, and Joshi et al 57) transformed geotags to words using reverse geo-coding technique. On the other hand, Yuan et al 150) used GPS trace data which is a series of geotags instead of using just a pinpoint geotag in order to classify images into several pre-defined events.…”

Section: Geotagged Imagesmentioning

confidence: 99%

[Invited Paper] A Review of Web Image Mining

Yanai

2015

MTA

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In this paper, we review works related to big visual data on the Web in the literature of computer vision and multimedia research regarding the following points: (1) Web image acquisition for construction of visual concept database for image/video recognition, (2) Web image application for visual concept analysis and data-driven computer graphics, and (3) real-world sensing through Web images to detect location-dependent and event-related visual information.

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Section: Geotagged Imagesmentioning

confidence: 99%

[Invited Paper] A Review of Web Image Mining

Yanai

2015

MTA

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“…As mentioned, electronic landmarks can be used by devices for navigational tasks. A number of electronic resources are now being geo‐tagged with a location which is related to the contents of the resource (Yaegashi and Yanai ). Such geo‐tagged resources can be photographs, textual descriptive or audio recordings.…”

Section: Literature Review and Rationalementioning

confidence: 99%

The Role of Contextual Info‐Marks in Navigating a Virtual Rural Environment

Rousell¹,

Jarvis²,

Brunsdon

2015

Transactions in GIS

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Navigation is a task performed in both large and small scale environments. Landmarks within an environment are of great benefit to these navigational tasks, but in large rural environments such landmarks may be sparse. It has been shown that landmarks need not be purely visual and that a change in context for a feature can make it become a landmark against its surroundings (such as being provided with significant meaning). Such meaning could be added through personal experience or by informing the observer via some form of communication. To investigate the effects of providing such contextual information on navigational performance, experiments were conducted in a large rural virtual environment where the delivery method of the information was varied between onscreen and PDA display. Users were instructed to perform a route tracing navigation task. In some instances users were presented with textual information about specific locations within the environment which appeared when they were in the vicinity of the location. Both quantitative and qualitative data were collected and analyzed, with results indicating that although the actual performance in the task was not significantly improved, users felt that their performance was better and the task easier when they were presented with the contextual information.

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“…It is a just 2-dimensional vector. To convert a 2-d vector into more rich representation, [14] and [22] converted geotags into visual information from the sky using aerial images, and [10] transformed geotags to words using reverse geo-coding technique. On the other hand, [26] used GPS trace data which is a series of geotags instead of using just a pinpoint geotag in order to classify images into several pre-defined events.…”

Section: Related Workmentioning

confidence: 99%

A visual analysis of the relationship between word concepts and geographical locations

Yanai

Kawakubo

Qiu

2009

Proceedings of the ACM International Conference on Image and Video Retrieval

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In this paper, we describe two methods to analyze the relationship between word concepts and geographical locations by using a large amount of geotagged images on the photo sharing Web sites such as Flickr.Firstly, we propose using both image region entropy and geolocation entropy to analyze relations between location and visual features, and in the experiment we found that concepts with low image entropy tends to have high geo-location entropy and vice versa.Secondly, we propose a novel method to select representative photographs for regions in the worldwide dimensions, which helps detect cultural differences over the world regarding word concepts with high geo-location entropy. In the proposed method, at first, we extracts the most relevant images by clustering and evaluation on the visual features. Then, based on geographic information of the images, representative regions are automatically detected. Finally, we select and generate a set of representative images for the representative regions by employing the Probabilistic Latent Semantic Analysis (PLSA) modelling. The results show the ability of our approach to mine regional representative photographs and cultural differences over the world.

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Can Geotags Help Image Recognition?

Cited by 10 publications

References 9 publications

[Invited Paper] A Review of Web Image Mining

[Invited Paper] A Review of Web Image Mining

The Role of Contextual Info‐Marks in Navigating a Virtual Rural Environment

A visual analysis of the relationship between word concepts and geographical locations

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