“Narrative image composition using objective and subjective tagging” by Withana, Matsui, Sugimoto, Harada and Inakage
Conference:
Type:
Entry Number: 92
Title:
- Narrative image composition using objective and subjective tagging
Presenter(s)/Author(s):
Abstract:
With recent advancements in digital photography, data storage and network technologies, publishing and sharing of digital images in Internet has been drastically increased. High popularity and growth of internet image libraries such as Flickr and Picasa are good examples for these trends. In order to enable easy browsing and searching, online storages store meta-data in the form of keywords to describe images. Meta-data could be a general description of the image, a specific tag or an annotation to describe spatial information within the image. In order to ease and improve the efficiency of tagging process, image processing and analysis algorithms has been combined to manual tagging systems [Yang et al. 2009]. Furthermore, meta-data can be used to create interesting presentations of images. Specially in exhibition displays, automated slide shows and digital photo frames, meta data are used to group related images and present them under different categories. However, presentations generated by most of the existing systems are limited to sequential displaying of individual images as correlated groups. In this paper we present a system that composite digital images in a narrative fashion utilizing objective and subjective tagging information. Proposed system can extract a region from one image and composite it into another image according to available meta-data. As a proof of concept we created a right to left continuous image panning application using Adobe Flash which combines different images according to their similarities and composite them together to create a narrative image presentation.
References:
Segaran, T. 2007. Programming Collective Intelligence. O’Reilly Media. Google ScholarDigital Library
Yang, K., Wang, M., and Zhang, H.-J. 2009. Active tagging for image indexing. In Proceedings of the IEEE International Conference on Multimedia and Expo, ICME, IEEE, 1620–1623. Google ScholarDigital Library
