w4 is a real time visual surveillance system for detecting and tracking multiple people and monitoring their activities in an outdoor environment. It operates on monocular gray-scale video imagery, or on video imagery from an infrared camera. W4 employs a combination of shape analysis and tracking

Abstract — This paper presents a set of techniques used in a real-time visual surveillance system. The system is implemented on a low-cost embedded DSP platform that is designed to work with stationary video sources. It consists of detection, a tracking and a classification module. The detector

This paper describes a new real-time approach for detecting changes in grey level image sequences, which were taken from stationary cameras. This new method combines a temporal difference method with an adaptive background model subtraction scheme. When changes in illumination occur, the background

a large-scale, real-time, surveillance and control application on a wireless sensor network. The task was to track multiple human targets walking through a 5041 square meter sensor field and dispatch simulated pursuers to capture them. We employed a multi-target tracking algorithm that was a

This paper presents a novel method of utilizing observed history for detecting abnormal behaviors in surveillance applications. An unsupervised algorithm is proposed to detect abnormal behaviors and re-train itself in real-time. Motion vectors of objects are estimated using the optical flow method

Abstract—An autonomous Internet Protocol (IP) camera based object tracking and behaviour identification system, capable of running in real-time on an embedded system with limited memory and processing power is presented in this paper. The main contribution of this work is the integration

Abstract. This paper introduced a human surveillance system which integrated the face understanding technologies to recognize personal identities in real time. We proposed a coarse-to-fine strategy to find out faces quickly and accurately. The global features of faces are used to reduce the search

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Abstract. This paper introduced a human surveillance system which integrated the face understanding technologies to recognize personal identities in real time. We proposed a coarse-to-fine strategy to find out faces quickly and accurately. The global features of faces are used to reduce the search

Many of the current applications proposed for wireless ad-hoc sensor networks are targeted toward low data rate monitoring applications, where data is gathered from the network and analyzed in a batch offline. The next generation