Public Space Behavior Modeling With Video and Sensor Analytics

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Abstract

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.

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