10-10-2012, 02:07 PM
Video Compression Motion Estimation
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Motion Estimation
Various image sequence analysis applications such as
segmentation, extraction of 3-D structure and motion,
pattern tracking and recognition and robot navigation;
Development of powerful processing algorithms.
n Filtering
Noise suppression and deblurring for improved visual
quality, and high-quality freeze-frame applications such
as image analysis and hardcopy from video;
Noise suppression for efficient postprocessing (e.g., data
compression).
Data Compression
Efficient storage and transmission of video data
in the areas of
Entertainment (motion picture film, Advanced TV);
Multimedia;
Education;
Personal communications (video-phone, videoconferencing);
Medical and scientific research;
Spatiotemporal Interpolation
Reconstruction of high-resolution still
frames from a sequence of images at a
lower spatial resolution (spatial resolution
improvement);
Frame interpolation
Video format conversion for interoperability among
video systems (e.g., frame rate upconversion of 24
frames/sec motion picture film to 60 frames/sec video
signal for advanced TV applications)
MOTION ESTIMATION
In general, we speak of motion of objects in
3-D real world.
In this section, we are concerned with the
"projected motion" of 3-D objects onto the 2-D
plane of an imaging sensor.
By motion estimation, we mean the estimation
of the displacement (or velocity) of image
structures from one frame to another in a timesequence
of 2-D images.
General Remarks on Optical Flow
Is it always possible to relate 3-D motion to
optical flow ?
Optical flow may be zero even when the 3-D object
is in motion.
(Imagine a rotating sphere with a perfectly uniform
surface distribution.
In this case, the sphere's image does not change in time,
and thus the apparent 2-D motion is zero.)