• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1236-1251
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• 2013

Sharing geo-tagged photos has been a hot social activity in the daily life because these photos not only contain geo information but also indicate people's hobbies, intention and mobility patterns. However, the present raw geo-tagged photo routes cannot provide information as enough as complete GPS trajectories due to the defects hidden in them. This paper mainly aims at analyzing the large amounts of geo-tagged photos and proposing a novel travel route restoring method. In our approach we first propose an Interest Measure Ratio to rank the hot spots based on density-based spatial clustering arithmetic. Then we apply the Hidden Semi-Markov model and Mean Value method to demonstrate migration discipline in the hot spots and restore the significant region sequence into complete GPS trajectory. At the end of the paper, a novel experiment method is designed to demonstrate that the approach is feasible in restoring route, and there is a good performance.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.5 no.5
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• pp.167-176
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• 2015

Due to the variety of tourist attractions, many people of the world are visiting annually in Mediterranean area. In this paper, we analyze Mediterranean tourism impact by specific events such as the Arab Spring. In details, we make several density maps based on the position and time information of the geo-tagged photos extracted from Panoramio which is a representative photo sharing website. These density maps should be used to analyze how can specific events affect on Mediterranean tourism. To do this, first, a spatial database is constructed using geo-tag and time information of photo data extracted from Panoramio. Using GIS tool, then, several density maps are produced after performing density process based on spatial databases. Based on these density maps, finally, we analyze visually on Mediterranean tourism impact according to before, progress, and after of the Arab Spring.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.57-61
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• 2019

Nowadays, portable digital cameras such as smart phone cameras are being popularly used for entertainment and visual information recording. Given a database of geo-tagged images, a visual location recognition system can determine the place depicted in a query photo. One of the most common visual location recognition approaches is the bag-of-words method where local image features are clustered into visual words. In this paper, we propose a new bag-of-words-based visual location recognition algorithm using time-series streetview database. The proposed algorithm selects only a small subset of image features which will be used in image retrieval process. By reducing the number of features to be used, the proposed algorithm can reduce the memory requirement of the image database and accelerate the retrieval process.