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CVPR
2009
IEEE
15 years 5 days ago
Understanding Videos, Constructing Plots - Learning a Visually Grounded Storyline Model from Annotated Videos
Analyzing videos of human activities involves not only recognizing actions (typically based on their appearances), but also determining the story/plot of the video. The storyline...
Abhinav Gupta (University of Maryland), Praveen Sr...
CVPR
2009
IEEE
13 years 11 months ago
Understanding videos, constructing plots learning a visually grounded storyline model from annotated videos
Analyzing videos of human activities involves not only recognizing actions (typically based on their appearances), but also determining the story/plot of the video. The storyline ...
Abhinav Gupta, Praveen Srinivasan, Jianbo Shi, Lar...
MM
2009
ACM
199views Multimedia» more  MM 2009»
13 years 9 months ago
Consumer video retargeting: context assisted spatial-temporal grid optimization
Pervasive multimedia devices require accurate video retargeting, especially in connected consumer electronics platforms. In this paper, we present a context assisted spatialtempor...
Liang Shi, Jinqiao Wang, Lingyu Duan, Hanqing Lu
WAPCV
2007
Springer
13 years 11 months ago
Language Label Learning for Visual Concepts Discovered from Video Sequences
Computational models of grounded language learning have been based on the premise that words and concepts are learned simultaneously. Given the mounting cognitive evidence for conc...
Prithwijit Guha, Amitabha Mukerjee
PAMI
2006
229views more  PAMI 2006»
13 years 4 months ago
A Coherent Computational Approach to Model Bottom-Up Visual Attention
Visual attention is a mechanism which filters out redundant visual information and detects the most relevant parts of our visual field. Automatic determination of the most visually...
Olivier Le Meur, Patrick Le Callet, Dominique Barb...