Image Processing Reference
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FIGURE 1 Outline of the proposed similar play estimating method.
3 1D degeneration from videos
There are many degeneration methods. Some works use the temporal slices [ 9 , 16 , 17 ] . The tem-
poral slices are easy to make and represent videos in small representation. The temporal slice
is the sequence of the set of selected pixels in frames. There is no information about other
pixels. These works make the temporal slices from color and textures in videos.
In this paper, we makes 1D degenerated representation using the statistical features of the
set of pixels. The main statistical features are mean, mode, and median. We uses the mean for
making 1D degeneration [ 9 ] . For treating sports, the motions in videos are important.
3.1 Motion Extraction from MPEG Videos and Construction of
Space-Time Image
From an MPEG video, we get a two-dimensional image describing motion compensation vec-
tors in a video. In the following, we abbreviate space-time image as ST image. The ST image
has a space axis and time axis. The ST image represents the sequence of frames in one two-di-
mensional image. The ST image is a very compact description of a video, and it is easy to treat.
3.2 Motion Compensation Vectors from MPEG Videos
First, we must have the motions in an MPEG video. An MPEG video is a sequence of GOP
(Group of Pictures). Each GOP is starting from I-frame, and has B-frames and P-frames. The
motion compensation vector is block wise. The block size is 16 × 16. There is a 640 × 480 MPEG
video. The image of motion compensation vector is only 40 × 30 pixels.
3.3 Space-Time Image
We have the motion vector (two-dimensional) on every motion compensation block. The
amount of information is 2/16 × 16 × 3 of the original color video. This is very small comparing
with the original color frames. The baseball games can long about 2 h. This video has 200k
frames. If we compare frame by frame, there needs a huge computation. There is a large dii-
culty to retrieve similar parts of a video.
We can retrieve similar parts of videos using classical representative frame wise video re-
trieve method. However, it is difficult to retrieve similar part of videos based on the player's
motions, because motion leads a change of subsequent frames.

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