Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/41346
Title: Using camera settings templates ("Scene Modes") for image scene classification of photographs taken on manual/expert settings
Authors: Ku, W. 
Kankanhalli, M.S. 
Lim, J.-H.
Keywords: Contextual information
EXIF
Image scene classification
Scene modes
Issue Date: 2007
Citation: Ku, W.,Kankanhalli, M.S.,Lim, J.-H. (2007). Using camera settings templates ("Scene Modes") for image scene classification of photographs taken on manual/expert settings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4810 LNCS : 10-17. ScholarBank@NUS Repository.
Abstract: The automatic point-and-click mode of Digital Still Cameras (DSCs) may be a boon to most users whom are simply trigger-happy. However, this automatic mode may not generate the best photos possible or be even applicable for certain types of shots, especially those that require technical expertise. To bridge this gap, many DSCs now offer "Scene Modes" that would easily allow the user to effortlessly configure his camera to specifically take certain types of photos, usually resulting in better quality pictures. These "Scene Modes" provide valuable contextual information about these types of photos and in this paper, we examine how we could make use of "Scene Modes" to assist in generic Image Scene Classification for photos taken on expert/manual settings. Our algorithm could be applied to any image classes associated with the "Scene Modes" and we demonstrated this with the classification of fireworks photos in our case study. © Springer-Verlag Berlin Heidelberg 2007.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/41346
ISBN: 9783540772545
ISSN: 03029743
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.