MSU Scene Change Detector (SCD)

Common Description

Scene Change Detector is made to automatic identification of scene boundaries in video sequence.

Change Log

[!] — Known bug
[+] — New Feature
[*] — Other

Version 1.2
[*] Windows Vista & Windows 7 support implemented

Version 1.1
[*] Visualization bug fixed for non-stadard resolution video

Version 1.0
[+] First plugin release

Usage

The plugin implements four algorithms of similarity measurements between two adjacency frames in video sequence:

  1. Pixel-level frames comparison
  2. Global Histogram comparison
  3. Block-Based Histogram comparison
  4. Motion-Based similarity measure

The choice of the algorithm can be made in Settings. Numbers from 1 up to 4 corresponds to each algorithm.

Default and recommended value is 3 (Block-Based Histogram).

Visualisation

Y-plane is drawing during the visualization. Brightness of scene boundary frames is increased.

Example of visualization:

Plots

Metric’s plot is making after all measurements. “One” value means that current frame is the first frame in scene, other frames have “zero” values. Sequence average value is the number of detected scene changes.

Plot's example
Plot's example

Algorithm

Pixel-level comparison

Similarity measure of two frames is the sum of absolute differences (SAD) between corresponding pixels values.

Global Histogram

The histogram is obtained by counting the number of pixels in frame with specified brightness level. The difference between two histograms is then determined calculating SAD of number of pixels on each brightness level.

Block-Based Histogram

Each frame is divided into 16x16 pixel blocks. Brightness distribution histogram is constructed for each block. Then similarity measure for each block is obtained. Average value of these measures is accepted as a frames similarity measure.

Motion-Based

Motion Estimation algorithm with block size 16x16 pixels is performed for two adjacency frames at the first stage. After that average value of motion vector errors is accepted as a finally similarity measure.

Download

Contacts

E-mail: video-measure@graphics.cs.msu.ru

10 May 2017
See Also
Automatic local color correction in S3D video
Stereo video may contain a huge color discrepancy. Most of the problems are hard to eliminate because of possible different distortions in each area in the frame.
MSU Video Quality Measurement Tool: Why upgrade?
MSU Video Quality Measurement Tool (PSNR, MSE, VQM, SSIM)
MSU Video Quality Measurement Tool (VQMT) is a program for objective video quality assessment.
MSU VQMT Subjective quality correlation
Comparison provided for the most popular metrics: PSNR, SSIM, 3-SSIM, MS-SSIM and new stSSIM
MSU Video Quality Measurement Tool: SDK
MSU Perceptual Video Quality: Subjective video quality methods information
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