Intelligent Surveillance for Understanding Events in Urban Traffic Environments

Abstract

The main goal of intelligent surveillance consists in providing security systems with the skills required for correctly detecting and analyzing events in monitored environments. Since these environments are complex and the information is distributed through them, the use of agent-based approaches has become more and more popular when monitoring moving objects. This paper describes how an existing agent platform has been adopted and used to give support to intelligent surveillance systems. Agents deployed by means of this platform implement a behavior-based model that is flexible enough to deal with the challenges that monitored environments pose. Two case studies of urban traffic environments are discussed to prove the feasibility of the proposal.

An online graph-based anomalous change detection strategy for unsupervised video surveillance

“…These intelligent surveillance methods provide better performance than analog/digital surveillance systems, but there are still some drawbacks. Methods based on image subtraction are relatively simple to implement but very susceptible to abnormal situations, such as static/dynamic changes, image brightness changes, and noise, because they depend on a reference image [18][19][20]. Alternatively, for machine learning-based detection algorithms, highperformance hardware is required due to the demand for high levels of computation ability in the learning process, and a vast amount and wide variety of data learning processes are also involved [21][22][23].…”

Advanced seismic signal processing techniques for detection and bearing estimation of footsteps and vehicular signals

“…Surveillance is defined as the continuous or periodic monitoring of person, vehicles, places or objects to obtain information concerning the activities and/or identities of the individual for the purpose of managing or protecting them. Urban surveillance systems were initially established as vision-based intelligent transport systems [15][16][17] or intelligent indoor/outdoor surveillance system [18][19][20] using network of cameras. Subsequently, distributed sensor based surveillance systems were built for variety of applications including landslide detection [21,22], avalanche detection [23], forest intrusion detection [24], perimeter security [25] etc.…”

“…Urban surveillance systems initially started as intelligent transport systems [15][16][17] and intelligent indoor/outdoor surveillance system [18][19][20] using only vision-based sensors, i.e., cameras. The aim of vision-based surveillance systems, used in advanced traffic management systems, is to extract descriptions of several moving vehicles from video data.…”

“…19 Plot of (i) z-axis signal and (ii) W CorrDiff metric for(a) no vehicle in the backgound and W CorrDiff evaluated using N =1 s, (b) vehicle in the background and W CorrDiff evaluated using N =1 s and (c) vehicle in the background and W CorrDiff evaluated using N =150 ms. . .…”