Name
Abstract | ||
|---|---|---|
In this paper range flow estimation is extended to handle brightness changes in image data caused by inhomogeneous illumination. Standard range flow computes 3d velocity fields from range and intensity image sequences. To this end it combines a depth change model and a brightness constancy model. In this contribution, the brightness constancy model is exchanged by (1) a gradient constancy model, (2) a combination of gradient and brightness constancy constraint that has been used successfully for optical flow estimation in literature, and (3) a physics-based brightness change model. Insensitivity to brightness changes can also be achieved by prefiltering of the input intensity data. High pass or homomorphic filtering are the most well known approaches from literature. In performance tests therefore the well known version and the novel versions of range flow estimation are investigated on prefiltered or non-prefiltered data using synthetic ground-truth and real data from a botanical experiment. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-88682-2_39 | ECCV |
Keywords | Field | DocType |
image data,varying illumination,optical flow estimation,brightness change,input intensity data,depth change model,non-prefiltered data,brightness constancy constraint,gradient constancy model,brightness constancy model,range flow,physics-based brightness change model,velocity field,high pass,ground truth | Computer vision,Computer science,Flow (psychology),Flow estimation,High-pass filter,Optical flow estimation,Artificial intelligence,Homomorphic filtering,Brightness | Conference |
Volume | ISSN | Citations |
5302 | 0302-9743 | 9 |
PageRank | References | Authors |
0.54 | 24 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tobias Schuchert | 1 | 93 | 12.21 |
| Til Aach | 2 | 855 | 117.45 |
| Hanno Scharr | 3 | 430 | 37.92 |