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NIPS
2007
15 years 7 months ago
Congruence between model and human attention reveals unique signatures of critical visual events
Current computational models of bottom-up and top-down components of attention are predictive of eye movements across a range of stimuli and of simple, fixed visual tasks (such a...
Robert J. Peters, Laurent Itti
CVPR
2009
IEEE
17 years 1 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 (University of Maryland), Praveen Sr...
CVPR
2009
IEEE
17 years 1 months ago
Dense 3D Motion Capture for Human Faces
This paper proposes a novel approach to motion capture from multiple, synchronized video streams, specifically aimed at recording dense and accurate models of the structure and ...
Yasutaka Furukawa (University of Washington), Jean...
CVPR
2008
IEEE
16 years 8 months ago
Recognizing human actions using multiple features
In this paper, we propose a framework that fuses multiple features for improved action recognition in videos. The fusion of multiple features is important for recognizing actions ...
Jingen Liu, Saad Ali, Mubarak Shah
CVPR
2009
IEEE
16 years 1 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...