Browsing by Author "Bansode, R."

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    A spatial clustering approach for efficient landmark discovery using geo-tagged photos
    (Institute of Electrical and Electronics Engineers Inc., 2016) Deeksha, S.D.; Ashrith, H.C.; Bansode, R.; Kamath S․, S.S.
    Geo-tagged photos enable people to share their personal experiences while visiting various vacation spots through image sharing social networks like Flickr. The geo-tag information offers a wealth of information for capturing additional information on traveler behavior, trends, opinions and interests. In this paper, we propose a landmark discovery system that aims to discover popular tourist attractions in a city by assuming that the popularity of a tourist attraction is positively dependent on the visitor statistics and also the amount of tourist uploaded photos clicked on site. It is a known fact that places with lots of geo-tagged photos uploaded to Flickr are visited more often by social-media savvy tourists, who plan their trip based on others' experiences. We propose to build a system that identifies the most popular tourist places in a particular city by using geo-tagged photos collected from Flickr and recommend the same to the user. In this paper, we present the methodology of spatially clustering the geo-tagged images and present an analysis of algorithm performance in identifying landmarks and their popularity. © 2015 IEEE.
  • No Thumbnail Available
    Item
    A spatial clustering approach for efficient landmark discovery using geo-tagged photos
    (2016) Deeksha, S.D.; Ashrith, H.C.; Bansode, R.; Sowmya, Kamath S.
    Geo-tagged photos enable people to share their personal experiences while visiting various vacation spots through image sharing social networks like Flickr. The geo-tag information offers a wealth of information for capturing additional information on traveler behavior, trends, opinions and interests. In this paper, we propose a landmark discovery system that aims to discover popular tourist attractions in a city by assuming that the popularity of a tourist attraction is positively dependent on the visitor statistics and also the amount of tourist uploaded photos clicked on site. It is a known fact that places with lots of geo-tagged photos uploaded to Flickr are visited more often by social-media savvy tourists, who plan their trip based on others' experiences. We propose to build a system that identifies the most popular tourist places in a particular city by using geo-tagged photos collected from Flickr and recommend the same to the user. In this paper, we present the methodology of spatially clustering the geo-tagged images and present an analysis of algorithm performance in identifying landmarks and their popularity. � 2015 IEEE.