Name
Abstract | ||
|---|---|---|
We present the focal flow sensor. It is an unactuated, monocular camera that simultaneously exploits defocus and differential motion to measure a depth map and a 3D scene velocity field. It does so using an optical-flow-like, per-pixel linear constraint that relates image derivatives to depth and velocity. We derive this constraint, prove its invariance to scene texture, and prove that it is exactly satisfied only when the sensor's blur kernels are Gaussian. We analyze the inherent sensitivity of the ideal focal flow sensor, and we build and test a prototype. Experiments produce useful depth and velocity information for a broader set of aperture configurations, including a simple lens with a pillbox aperture. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-46487-9_41 | COMPUTER VISION - ECCV 2016, PT III |
Keywords | Field | DocType |
Optical Flow,Image Patch,Pinhole Camera,Differential Motion,Sensor Distance | Aperture,Computer vision,Pinhole camera,Simple lens,Image derivatives,Vector field,Computer science,Gaussian,Artificial intelligence,Depth map,Optical flow | Conference |
Volume | ISSN | Citations |
9907 | 0302-9743 | 2 |
PageRank | References | Authors |
0.36 | 16 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emma Alexander | 1 | 2 | 1.04 |
| Qi Guo | 2 | 43 | 12.11 |
| Sanjeev J. Koppal | 3 | 200 | 17.11 |
| Steven J. Gortler | 4 | 4205 | 366.17 |
| Todd Zickler | 5 | 1555 | 71.72 |