Euclidean path modeling for video surveillance
Image and Vision Computing
Performance analysis for gait in camera networks
AREA '08 Proceedings of the 1st ACM workshop on Analysis and retrieval of events/actions and workflows in video streams
Object Matching in Distributed Video Surveillance Systems by LDA-Based Appearance Descriptors
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Recovering network topology with binary sensors
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Continuous learning of a multilayered network topology in a video camera network
Journal on Image and Video Processing - Special issue on video-based modeling, analysis, and recognition of human motion
Finding camera overlap in large surveillance networks
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Continuously tracking objects across multiple widely separated cameras
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Time-Delayed Correlation Analysis for Multi-Camera Activity Understanding
International Journal of Computer Vision
Performance analysis for automated gait extraction and recognition in multi-camera surveillance
Multimedia Tools and Applications
Distributed tracking in a large-scale network of smart cameras
Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras
A learning approach to interactive browsing of surveillance content
Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras
Tracking and activity recognition through consensus in distributed camera networks
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
Event prediction in a hybrid camera network
ACM Transactions on Sensor Networks (TOSN)
Multimodal semantics extraction from user-generated videos
Advances in Multimedia
Intelligent multi-camera video surveillance: A review
Pattern Recognition Letters
Statistical inference of motion in the invisible
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Modeling Coverage in Camera Networks: A Survey
International Journal of Computer Vision
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We present an approach for inferring the topology of a camera network by measuring statistical dependence between observations in different cameras. Two cameras are considered connected if objects seen departing in one camera are seen arriving in the other. This is captured by the degree of statistical dependence between the cameras. The nature of dependence is characterized by the distribution of observation transformations between cameras, such as departure to arrival transition times, and color appearance. We show how to measure statistical dependence when the correspondence between observations in different cameras is unknown. This is accomplished by non-parametric estimates of statistical dependence and Bayesian integration of the unknown correspondence. Our approach generalizes previous work which assumed restricted parametric transition distributions and only implicitly dealt with unknown correspondence. Results are shown on simulated and real data. We also describe a technique for learning the absolute locations of the cameras with Global Positioning System (GPS) side information.