|
|
 |
| |
|
|
|
Effective Scene Change Detection by Using Statistical Analysis of Optical Flows |
|
|
|
PP: 177S-183S |
|
|
|
Author(s) |
|
|
|
Jung Lee et al,
|
|
|
|
Abstract |
|
|
| We present a novel method that exploits the statistical properties of optical flows to find
representative video frames that contain scene change moments in video contents. For effective
scene change detection, we first divide the optical flows into background and foreground groups.
Optical flow is a useful and effective method for tracking object motion between consecutive video
frames. By analyzing the variation of optical flows, we can detect rapid scene change between
consecutive frames. A scene change probability for each frame is computed by applying some basic
statistical methods, such as average and standard deviation. Starting from the selected frames with
high probability, we find a clear image that contains no overlapping contents by inspecting the
moment that optical flow values changes slowly and steadily. Experimental results show the
robustness and effectiveness of our method. |
|
|
|
|
|
|
|
