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MPEG-7 Motion Descriptors. Reference. ISO/IEC JTC1/SC29/WG11 N4031 ISO/IEC JTC1/SC29/WG11 N4062 MPEG-7 Visual Motion Descriptors (IEEE Transactions on Circuits and Systems for Video Technology) Video Indexing using Descriptors of Spatial Distribution of Motion Activity

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Reference
Reference

  • ISO/IEC JTC1/SC29/WG11 N4031

  • ISO/IEC JTC1/SC29/WG11 N4062

  • MPEG-7 Visual Motion Descriptors

    (IEEE Transactions on Circuits and Systems for Video Technology)

  • Video Indexing using Descriptors of Spatial Distribution of Motion Activity

    (submitted to IEEE Transactions on Circuits and Systems for Video Technology)


Introduction
Introduction

  • MPEG-7, formally named “Multimedia Content Description Interface”, is a standard for describing features of multimedia content.

  • Users can search, browse, and retrieve that content more efficiently and effectively than they could using today’s mainly text-based search engines.

  • We describes tools and techniques for representing motion information in the context of MPEG-7.



Camera motion
Camera Motion

  • This descriptor characterizes 3-D camera motion parameters.

  • It supports the following well-known basic camera operations:fixed,panning,tracking, tilting,booming,zooming,dollying and rolling.


Motion trajectory
Motion Trajectory

  • Motion trajectory is a high-level feature, defined as the spatio-temporal localization, of one of its representative point of this object.

  • The descriptor is essentially a list of keypoints along with a set of optional interpolating function that describe the path of the object between keypoints.



Parametric motion
Parametric Motion trajectory identified as dangerous; in sports, specific actions can be recognized.

  • This descriptor addresses the motion of objects in video sequences as a 2D parametric model.

  • Translational models: vx(x, y) = a1 vy(x, y) = a2

  • Rotation/scaling models: vx(x, y) = a1 + a3x + a4y vy(x, y) = a2 - a4x + a3y

  • Affine models: vx(x, y) = a1 + a3x + a4y vy(x, y) = a2 + a5x + a6y

  • Perspective models: vx(x, y) = (a1 + a3 x +a4 y) / (1 + a7 x +a8 y) vy(x, y) = (a2 + a5 x +a6 y) / (1 + a7 x +a8 y)

  • Quadratic models: vx(x, y) = a1 + a3 x + a4 y + a7 xy + a9 x2 + a10 y2 vy(x, y) = a2 + a5 x + a6 y + a8 xy + a11 x2 + a12 y2


Motion activity
Motion Activity trajectory identified as dangerous; in sports, specific actions can be recognized.

  • Video content in general spans the gamut from high to low activity, therefore we need a descriptor that enables us to accurately express the activity of a given sequence/shot.

  • The activity descriptor includes the following attributes:

    • Intensity of Activity

    • Direction of Activity (optional)

    • Spatial Distribution of Activity (optional)

    • Temporal Distribution of Activity (optional)


Intensity of activity
Intensity of Activity trajectory identified as dangerous; in sports, specific actions can be recognized.

  • Expressed by an 3-bit integer lying in the range 1~5.

  • A high value of intensity indicates high activity while a low value of intensity indicates low activity.

  • For example, a still shot has a low intensity of activity while a “fast break” basketball shot has a high intensity of activity.



1 vector magnitudes, appropriately normalized by the frame resolution.– very low activity2 – low activity3 – medium activity4 – high activity5 – very high activity

if(std_dev<t1) intensity = 1;else if(std_dev<t2) intensity = 2;else if(std_dev<t3) intensity = 3;else if(std_dev<t4) intensity = 4;else intensity = 5;

t1 = 0.257*l/F

t2 = 0.706*l/F

t3 = 1.280*l/F

t4 = 2.111*l/F

diagonal length l = sqrt(w*w + h*h)

F is the frame rate in frames/second.


Spatial distribution of activity
Spatial distribution of Activity vector magnitudes, appropriately normalized by the frame resolution.

  • The descriptor indicate whether the activity is spread across many regions or restricted to one large region.

  • It is an indication of the number and size of “active” regions in a frame.

  • For example, a talking head sequence would have one large active region, while an shot of busy street would have many small active regions.


Thresholded motion vector magnitude matrix
Thresholded motion vector magnitude matrix vector magnitudes, appropriately normalized by the frame resolution.


  • Recording the length of zero runs in a raster scan order over the thresholded motion vector magnitude matrix.

  • Short runs are defined as runs that are less than 1/3 of the frame width.

  • 1/3 < medium runs < 2/3

  • Long runs > 2/3

  • The element consists of three field: Nsr, Nmr, Nlr,which contain the numbers of short, medium, and long runs of zeros,respectively.


The dark area consists of macroblocks that get non-zero values after thresholding.

The remaining area consists of macroblocks that get “zero out” after thresholding.


With smaller,widely spaced objects note that there are more long-run lengths and medium run-lengths


Direction of activity
Direction of Activity long-run lengths and medium run-lengths

  • While a video shot may give several objects with different activities, we can often identify a dominant direction.

  • /* quantize angle using uniform 3 bit quantization over 0-360 degrees i.e. 0,45,90,135,180,225,270,315 */ if((f_angle>=-22.5)&&(f_angle<22.5)) direction=0; else if((f_angle>=22.5)&&(f_angle<67.5)) direction=1; else if((f_angle>=67.5)&&(f_angle<112.5)) direction=2; else if((f_angle>=112.5)&&(f_angle<157.5)) direction=3; else if((f_angle>=157.5)&&(f_angle<202.5)) direction=4; else if((f_angle>=202.5)&&(f_angle<247.5)) direction=5; else if((f_angle>=247.5)&&(f_angle<292.5)) direction=6; else if((f_angle>=292.5)&&(f_angle<337.5)) direction=7;


Temporal distribution of activity
Temporal Distribution of Activity long-run lengths and medium run-lengths

  • Express the variation of activity over the duration of the video segment/shot.

  • A histogram consisting of 5 bin, where histogram bins N0,N1,N2,N3,and N4 correspond to intensity value of 1,2,3,4,and 5 respectively.

  • Each value is the percentage of occurrences of each quantized intensity level.


Usage and applications
Usage and Applications long-run lengths and medium run-lengths

  • Video browsing:

    The motion-activity intensity descriptor enables selection of the video segments of a program based on intensity of motion activity.

  • Content-based querying of video databse:

    We can use motion activity to separate the high and low motion parts of the video sequence and or as a first stage content filter.


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