TY - GEN
T1 - e-Silkroad
T2 - 1st ACM Workshop on Connected Multimedia, CMM'10, Co-located with ACM Multimedia 2010
AU - Wang, Qing
AU - Qi, Xiaozhen
AU - Xu, Jiong
PY - 2010
Y1 - 2010
N2 - With the development of Web2.0, very large scale resources of multimedia have emerged in the internet. In this paper, we present a novel framework of building a tour guide based on the online knowledge resources, e.g., e-Silkroad, a photographic guide of traditional Silkroad. The tour guide is jointly established by text information from Wikipedia and images from flickr website. Our method starts from a keyword "silkroad" in Wiki and typical cities are extracted and regarded as the key threads of the guide. Then a great number of images and their description tags are downloaded from Flickr website. To highlight the most interesting place and more active tourist, the framework computes the hot spots and photographers in the dataset. To introduce each place along the silkroad, all the images are classified into four categories by its content, including person, food, man-made, and sights. Finally, the images are registered into Google Maps according to the geog-tag descriptions along silk routes to generate e-Silkroad. In our evaluation experiment, 20676 images were downloaded from 35 key cities along silkroad. Experimental results show that it is effective from social media to cultural tourism under the connected environment.
AB - With the development of Web2.0, very large scale resources of multimedia have emerged in the internet. In this paper, we present a novel framework of building a tour guide based on the online knowledge resources, e.g., e-Silkroad, a photographic guide of traditional Silkroad. The tour guide is jointly established by text information from Wikipedia and images from flickr website. Our method starts from a keyword "silkroad" in Wiki and typical cities are extracted and regarded as the key threads of the guide. Then a great number of images and their description tags are downloaded from Flickr website. To highlight the most interesting place and more active tourist, the framework computes the hot spots and photographers in the dataset. To introduce each place along the silkroad, all the images are classified into four categories by its content, including person, food, man-made, and sights. Finally, the images are registered into Google Maps according to the geog-tag descriptions along silk routes to generate e-Silkroad. In our evaluation experiment, 20676 images were downloaded from 35 key cities along silkroad. Experimental results show that it is effective from social media to cultural tourism under the connected environment.
KW - Image classification
KW - Silkroad
KW - Social media
KW - Sparse representation
KW - Tour guide
UR - http://www.scopus.com/inward/record.url?scp=78650434198&partnerID=8YFLogxK
U2 - 10.1145/1877911.1877920
DO - 10.1145/1877911.1877920
M3 - 会议稿件
AN - SCOPUS:78650434198
SN - 9781450301725
T3 - CMM'10 - Proceedings of the 1st ACM Workshop on Connected Multimedia, Co-located with ACM Multimedia 2010
SP - 27
EP - 32
BT - CMM'10 - Proceedings of the 1st ACM Workshop on Connected Multimedia, Co-located with ACM Multimedia 2010
Y2 - 29 October 2010 through 29 October 2010
ER -