Title
High-Level Event Recognition In Unconstrained Videos
Keywords
Fusion; Multimedia event detection; Multimodal features; Recognition; Unconstrained videos; Video events
Abstract
The goal of high-level event recognition is to automatically detect complex high-level events in a given video sequence. This is a difficult task especially when videos are captured under unconstrained conditions by non-professionals. Such videos depicting complex events have limited quality control, and therefore, may include severe camera motion, poor lighting, heavy background clutter, and occlusion. However, due to the fast growing popularity of such videos, especially on the Web, solutions to this problem are in high demands and have attracted great interest from researchers. In this paper, we review current technologies for complex event recognition in unconstrained videos. While the existing solutions vary, we identify common key modules and provide detailed descriptions along with some insights for each of them, including extraction and representation of low-level features across different modalities, classification strategies, fusion techniques, etc. Publicly available benchmark datasets, performance metrics, and related research forums are also described. Finally, we discuss promising directions for future research.
Publication Date
6-1-2013
Publication Title
International Journal of Multimedia Information Retrieval
Volume
2
Issue
2
Number of Pages
73-101
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/s13735-012-0024-2
Copyright Status
Unknown
Socpus ID
84986185450 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84986185450
STARS Citation
Jiang, Yu Gang; Bhattacharya, Subhabrata; Chang, Shih Fu; and Shah, Mubarak, "High-Level Event Recognition In Unconstrained Videos" (2013). Scopus Export 2010-2014. 7060.
https://stars.library.ucf.edu/scopus2010/7060