Name
Abstract | ||
|---|---|---|
Large networks of cameras have been increasingly employed to capture dynamic events for tasks such as surveillance and training. When using active cameras to capture events distributed throughout a large area, human control becomes impractical and unreliable. This has led to the development of automated approaches for online camera control. We introduce a new automated camera control approach that consists of a stochastic performance metric and a constrained optimization method. The metric quantifies the uncertainty in the state of multiple points on each target. It uses state-space methods with stochastic models of target dynamics and camera measurements. It can account for occlusions, accommodate requirements specific to the algorithms used to process the images, and incorporate other factors that can affect their results. The optimization explores the space of camera configurations over time under constraints associated with the cameras, the predicted target trajectories, and the image processing algorithms. The approach can be applied to conventional surveillance tasks (e.g., tracking or face recognition), as well as tasks employing more complex computer vision methods (e.g., markerless motion capture or 3D reconstruction). |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2530283 | TOSN |
Keywords | Field | DocType |
computer vision task,active camera network,active camera,online control,target dynamic,markerless motion capture,human control,camera configuration,camera measurement,online camera control,automated approach,target trajectory,new automated camera control,constrained optimization,3d reconstruction,mathematical model,face recognition,motion capture,computer model,indexing terms,three dimensional,image processing,stochastic model,computer vision | Motion capture,Computer vision,Facial recognition system,Computer science,Camera auto-calibration,Performance metric,Smart camera,Real-time computing,Artificial intelligence,Digital image processing,Constrained optimization,3D reconstruction | Journal |
Volume | Issue | ISSN |
10 | 2 | 1550-4859 |
Citations | PageRank | References |
6 | 0.45 | 32 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adrian Ilie | 1 | 166 | 15.20 |
| Greg Welch | 2 | 1595 | 186.21 |