Abstract
In this paper, we propose a system named “LHES” to detect location-based social events on flexible time scales and generate a hierarchical summary for the event. Particularly, we focus on social events that happened at landmarks. Flexible time scales include month, day, hour and minute. For each landmark, our LHES system generates a hierarchical (tree style) summary, in which the root node gives a snapshot of the entire event and child nodes span different time periods (beginning, ending, etc.) of the parent event. To generate such a summary, we use both visual cues (e.g., color, texture) and metadata (e.g., time stamp, image tags, titles and description). Our online demo is available at http://hed.apexlab.org.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Claudiu, S., Mihai, G., Wolfgang, N., Raluca, P.: Bringing order to your photos: event-driven classification of flickr images based on social knowledge. In: CIKM, pp. 189–198 (2010)
Hila, B., Mor, N., Luis, G.: Learning similarity metrics for event identification in social media. In: WSDM, pp. 291–300 (2010)
Junfeng, Y., Jia, C., Zejia, C., Yihe, Z., Shenghua, B., Zhong, S., Yong, Y.: Searching for diversified landmarks by photo. In: ACM Multimedia, pp. 1337–1338 (2012)
Liu, X., Huet, B.: EventEnricher: a novel way to collect media illustrating events. In: ICMR, pp. 303–304 (2013)
Songhao, Z., Junchi, Y., Yuncai, L.: Improving Semantic Scene Categorization by Exploiting Audio-Visual Features. In: ICIG, pp. 449–450 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Zhang, W., Chen, J., Shen, J., Yu, Y. (2014). Location-Based Hierarchical Event Summary for Social Media Photos. In: Ooi, W.T., Snoek, C.G.M., Tan, H.K., Ho, CK., Huet, B., Ngo, CW. (eds) Advances in Multimedia Information Processing – PCM 2014. PCM 2014. Lecture Notes in Computer Science, vol 8879. Springer, Cham. https://doi.org/10.1007/978-3-319-13168-9_27
Download citation
DOI: https://doi.org/10.1007/978-3-319-13168-9_27
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13167-2
Online ISBN: 978-3-319-13168-9
eBook Packages: Computer ScienceComputer Science (R0)