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CVPR
2009
IEEE
16 years 4 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
15 years 4 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...
ICC
2009
IEEE
182views Communications» more  ICC 2009»
15 years 4 months ago
Content Clustering Based Video Quality Prediction Model for MPEG4 Video Streaming over Wireless Networks
— The aim of this paper is quality prediction for streaming MPEG4 video sequences over wireless networks for all video content types. Video content has an impact on video quality...
Asiya Khan, Lingfen Sun, Emmanuel C. Ifeachor
CVPR
2008
IEEE
15 years 11 months ago
Human action recognition using Local Spatio-Temporal Discriminant Embedding
Human action video sequences can be considered as nonlinear dynamic shape manifolds in the space of image frames. In this paper, we address learning and classifying human actions ...
Kui Jia, Dit-Yan Yeung
CVPR
2012
IEEE
12 years 12 months ago
Learning object class detectors from weakly annotated video
Object detectors are typically trained on a large set of still images annotated by bounding-boxes. This paper introduces an approach for learning object detectors from realworld w...
Alessandro Prest, Christian Leistner, Javier Civer...