Performance of optical flow techniques
International Journal of Computer Vision
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
A System for Learning Statistical Motion Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Contour-Based Moving Object Detection and Tracking
ICCCN '05 Proceedings of the 14th International Conference on Computer Communications and Networks
Introduction to the Special Issue on Biometrics: Progress and Directions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Foreground Detection In Video Using Pixel Layers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video Behavior Profiling for Anomaly Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object motion detection using information theoretic spatio-temporal saliency
Pattern Recognition
Mining periodic behaviors for moving objects
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Training-Free, Generic Object Detection Using Locally Adaptive Regression Kernels
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image segmentation in video sequences: a probabilistic approach
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Guest Editorial: Special Issue on Human Detection and Recognition
IEEE Transactions on Information Forensics and Security - Part 2
Traffic monitoring and accident detection at intersections
IEEE Transactions on Intelligent Transportation Systems
Guest Editorial Introduction To The Special Issue On Automatic Target Detection And Recognition
IEEE Transactions on Image Processing
Hi-index | 0.00 |
We present a review of technologies relevant to public space surveillance and describe a pilot study to explore the challenges. The general purpose of this study is to capture and analyze behavior patterns and anomalies of people behavior in a public space. On the capture side, we explore a small array of networked cameras as well as an ultrasonic sensor array for measuring the height of walking persons. After capture, video and ultrasound signals are analyzed and statistics calculated for such measurements, including the duration and speed of the trajectory of each tracked person, and a person's height which is a useful biometric feature for tracking the person across multiple, non-overlapping camera views. These statistics are first analyzed offline to determine the expected patterns of measured values over many captured events. Based on the expected patterns, anomalies can be detected as outliers in real time. Since this is a broad-based pilot study, conclusions relate to the effectiveness of the capture modalities and approaches investigated. We discuss how we use these findings to guide our future work. © 2012 Alcatel-Lucent. © 2012 Wiley Periodicals, Inc.