In this set of experiments, we investigate applications of our algorithm to summarization of surveillance videos. The algorithm is modified to build the feature matrix using only H and S elements in the HSV color space. The sample videos are taken from CCTV Camera Pros
Video 1 shows a day view of a car, someone approaches the car and steals something from inside and runs away. Video 2 is similar but shot at night. For both videos the first frame which is totally dark and the final advertisements are dropped and not processed. From each a %1 summary is produced.
| Video | #Frames | Key Frames | Summary Image |
| #1 | 490 | 2, 4, 7, 146, 200 | summary1.bmp |
| #2 | 540 | 2, 4, 205, 416, 522 | summary2.bmp |
| #3 | 420 | 10, 132, 396, 416 | summary3.bmp |
Summary of Video 1 did not include any frames from the second half of the video. After comparing the sequence with that of Video 2, it was noticed that unlike Video 2, Video 1 starts when the person is in the scene. Therefore, the frames from the second half of the video seem 'normal' and not detected as significant frames. Therefore we tried Video 3 which similarly to Video1 is shot in day light but starts with no person in the scene.
