| Paper: | MP-P1.9 |
| Session: | Image and Video Storage and Retrieval II |
| Time: | Monday, September 17, 14:30 - 17:10 |
| Presentation: |
Poster
|
| Title: |
KEY-PLACES DETECTION AND CLUSTERING IN MOVIES USING LATENT ASPECTS |
| Authors: |
Maguelonne Héritier; CRIM | | |
| | Samuel Foucher; CRIM | | |
| | Langis Gagnon; CRIM | | |
| Abstract: |
We describe a new method to find and cluster recurrent key-places in a movie. It consists of an unsupervised classification of shots that are taking place in the same physical location (key-place). Our approach is based on finding links between key-frames belonging to a same key- place. We use a probabilistic latent space model over the possible match points between the image sets. This allows extracting significant groups of local descriptor matches that may represent characteristic elements of a key-place. A preliminary test on a full-length movie gives a recognition rate of 78.0% on the key-places clustering. |
