ISCAS
2008
IEEE
13 years 10 months ago
2008
IEEE
—This paper presents a novel approach for automatic recognition of human activities from video sequences. We first group features with high correlations into Category Feature Vec...
ICMCS
2008
IEEE
13 years 10 months ago
2008
IEEE
The temporal correlation between adjacent video frames poses a severe challenges for video watermarking applications. Motioncoherent watermarking has been recognized as a strategy...
ICASSP
2008
IEEE
13 years 10 months ago
2008
IEEE
We present a novel video fingerprinting method based on subspace embedding. The proposed method is particularly robust against frame-rate conversion attacks and geometric attacks...
CCGRID
2008
IEEE
13 years 10 months ago
2008
IEEE
—The research area of Multimedia Content Analysis (MMCA) considers all aspects of the automated extraction of new knowledge from large multimedia data streams and archives. In re...
SIBGRAPI
2009
IEEE
13 years 11 months ago
2009
IEEE
—Network cameras, extensively used in video surveillance, often allow pan-tilt-zoom functionality and are also subject to wind load and mount vibrations, thus causing video frame...
ICIP
2009
IEEE
14 years 5 months ago
2009
IEEE
This paper proposes a motion-focusing method to extract key frames and generate summarization synchronously for surveillance videos. Within each pre-segmented video shot, the prop...
ICIP
2006
IEEE
14 years 5 months ago
2006
IEEE
This paper presents an efficient three-step algorithm to compute key frames for summarization and indexing of digital videos. In the preprocessing step, we remove the video frames...
CVPR
2007
IEEE
14 years 6 months ago
2007
IEEE
The task of registering video frames with a static model is a common problem in many computer vision domains. The standard approach to registration involves finding point correspo...
CVPR
2005
IEEE
14 years 6 months ago
2005
IEEE
The appearance of dynamic scenes is often largely governed by a latent low-dimensional dynamic process. We show how to learn a mapping from video frames to this lowdimensional rep...