Probability, random processes, and estimation theory for engineers
Probability, random processes, and estimation theory for engineers
Self-calibration from multiple views with a rotating camera
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach
A Scalable Image-Based Multi-Camera Visual Surveillance System
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
Automated multi-camera planar tracking correspondence modeling
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
A design methodology for selection and placement of sensors in multimedia surveillance systems
Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
Design of multimedia surveillance systems
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Assigning cameras to subjects in video surveillance systems
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Event prediction in a hybrid camera network
ACM Transactions on Sensor Networks (TOSN)
Hi-index | 0.00 |
Wide-area context awareness is a crucial enabling technology for next generation smart buildings and surveillance systems. It is not practical to cover an entire building with cameras, however it is difficult to infer missing information when there are significant gaps in coverage. As a solution, we advocate a class of hybrid perceptual systems that builds a comprehensive model of activity in a large space, such as a building, by merging contextual information from a dense network of ultra-lightweight sensor nodes with video from a sparse network of high-capability sensors. In this paper we explore the task of automatically recovering the relative geometry between a pan-tilt-zoom camera and a network of one-bit motion detectors. We present results for the recovery of geometry alone, and also recovery of geometry jointly with simple activity models. Because we don't believe a metric calibration is necessary, or even entirely useful for this task, we formulate and pursue the novel goal we term functional calibration. Functional calibration is the blending of geometry estimation and simple behavioral model discovery. Accordingly, results are evaluated in terms of the ability of the system to automatically foveate targets in a large, non-convex space, not in terms of pixel reconstruction error.