Calibrating a wide-area camera network with non-overlapping views using mobile devices
Abstract
In a wide-area camera network, cameras are often placed such that their views do not overlap. Collaborative tasks such as tracking and activity analysis still require discovering the network topology including the extrinsic calibration of the cameras. This work addresses the problem of calibrating a fixed camera in a wide-area camera network in a global coordinate system so that the results can be shared across calibrations. We achieve this by using commonly available mobile devices such as smartphones. At least one mobile device takes images that overlap with a fixed camera's view and records the GPS position and 3D orientation of the device when an image is captured. These sensor measurements (including the image, GPS position, and device orientation) are fused in order to calibrate the fixed camera. This article derives a novel maximum likelihood estimation formulation for finding the most probable location and orientation of a fixed camera. This formulation is solved in a distributed manner using a consensus algorithm. We evaluate the efficacy of the proposed methodology with several simulated and real-world datasets.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 01, 2014
- Source ID
- 10.1145/2530284
Entities
People
- B.S. Manjunath
- Santhoshkumar Sunderrajan
- Thomas Kuo
- Zefeng Ni
Organizations
- Office of Naval Research
- University of California, Santa Barbara