Driving saccade to pursuit using image motion
International Journal of Computer Vision
Approximation algorithms for time-dependent orienteering
Information Processing Letters
VS '98 Proceedings of the 1998 IEEE Workshop on Visual Surveillance
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Face Cataloger: Multi-Scale Imaging for Relating Identity to Location
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
A Scalable Image-Based Multi-Camera Visual Surveillance System
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
A master-slave system to acquire biometric imagery of humans at distance
IWVS '03 First ACM SIGMM international workshop on Video surveillance
Scheduling an active camera to observe people
Proceedings of the ACM 2nd international workshop on Video surveillance & sensor networks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Acquiring Multi-Scale Images by Pan-Tilt-Zoom Control and Automatic Multi-Camera Calibration
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Pre-Attentive Face Detection for Foveated Wide-Field Surveillance
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
A reinforcement learning approach to active camera foveation
Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
Online control of active camera networks for computer vision tasks
ACM Transactions on Sensor Networks (TOSN)
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This paper considers the problem of scheduling an active observer to visit as many targets in an area of surveillance as possible. We show how it is possible to plan a sequence of decisions regarding what target to look at through such a foveal-sensing action. We propose a framework in which a pan/tilt/zoom camera executes saccades in order to visit, and acquire high resolution images (at least one) of, as many moving targets as possible before they leave the scene. An intelligent choice of the order of sensing the targets can significantly reduce the total dead-time wasted by the active camera and, consequently, its cycle time. We cast the whole problem into a dynamic discrete optimization framework. In particular, we will show that the problem can be solved by modeling the attentional gaze control as a kinetic traveling salesperson problem whose solution is approximated by iteratively solving time dependent orienteering problems.Congestion analysis experiments are reported demonstrating the effectiveness of the solution in acquiring high resolution images of a large number of moving targets in a wide area. The evaluation was conducted with a simulation of a dual camera system in a master-slave configuration. We also report on preliminary experiments conducted using live cameras in a real surveillance environment.