09-10-2012, 03:50 PM
Video Compression Motion Estimation
Video Compression.pdf (Size: 297.15 KB / Downloads: 49)
Applications
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.
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).
Spatiotemporal Interpolation
Reconstruction of high-resolution still
frames from a sequence of images at a
lower spatial resolution (spatial resolution
improvement);
n 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.)
Section Outline
Fundamental concepts in motion estimation
Image intensity conservation: The optical flow
constraint equation
Ambiguities resulting from intensity
conservation
The use of a priori information in motion
estimation
A classification of motion estimation
algorithms