not logged in. (login)
Placement and Control of Cameras in Video Sensor Networks
|
|
The goal of this project is to develop methods for determing the optimal position and choice of video cameras to cover a given area and to serve specific vision task(s), and algorithms for prediction, camera control, and scheduling of computer vision tasks within a networked collection of video cameras. A predictive framework is being developed that can accrue a statistical model of temporal associations between events of interest observed within a sensor network. Finally, algorithms are being formulated that can exploit the statistical models in scheduling sensor network resources to accomplish certain tasks, like tracking objects of interest, or identifying all individuals. |
|
Personnel: |
Related Publications
title
|
year
|
|
|
Liliana Lo Presti, Stan Sclaroff and Marco La Cascia , "Object matching in distributed video surveillance systems by LDA-based appearance descriptors ," Proc. of International Conf. on Image Analysis and Processing (ICIAP), 2009.
|
2009 |
|
|
||
|
Ugur Murat Erdem and Stan Sclaroff , "Automated camera layout to satisfy task-specific and floor plan-specific coverage requirements," Computer Vision and Image Understanding (CVIU), Vol. 103, pp 156-169, 2006.
|
2006 |
|
|
||
|
Ugur Murat Erdem and Stan Sclaroff , "Look there! Predicting where to look for motion in an active camera network," Proc. Int. Conf. on Advanced Video and Signal Based Surveillance (AVSS), pp 105-110, 2005.
|
2005 |
|
|
||
|
Ugur Murat Erdem and Stan Sclaroff , "Optimal Placement of Cameras in Floorplans to Satisfy Task Requirements and Cost Constraints," Proc. International Workshop on Omnidirectional Vision, Camera Networks and Non-classical Cameras, pp 30-41, 2004.
|
2004 |
|
|
||