Name
Abstract | ||
|---|---|---|
Motion estimation is usually based on the brightness constancy assumption. This assumption holds well for rigid objects with a Lambertian surface, but it is less appropriate for fluid and gaseous materials. For these materials a variant of this assumption, which we call the brightness conservation assumption should be employed. Under this assumption an object's brightness can diffuse to its neighborhood. We propose a method for detecting regions of dynamic texture in image sequences. Segmentation into regions of static and dynamic texture is achieved by using a level set scheme. The level set function separates the images into areas obeying brightness constancy and those which obey brightness conservation. Experimental results on challenging image sequences demonstrate the success of the segmentation scheme and validate the model. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-72823-8_73 | SSVM |
Keywords | Field | DocType |
level set scheme,image sequence,lambertian surface,brightness conservation,detecting region,brightness conservation assumption,dynamic texture,brightness constancy,segmentation scheme,level set function,brightness constancy assumption,optical flow,level set,motion estimation | Level set function,Computer vision,Segmentation,Image texture,Level set,Artificial intelligence,Motion estimation,Optical flow,Brightness,Mathematics | Conference |
Volume | ISSN | Citations |
4485 | 0302-9743 | 18 |
PageRank | References | Authors |
1.21 | 29 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tomer Amiaz | 1 | 78 | 4.44 |
| Sándor Fazekas | 2 | 242 | 9.74 |
| Chetverikov, D. | 3 | 956 | 99.89 |
| Nahum Kiryati | 4 | 1838 | 162.51 |