Sensor node localisation using a stereo camera rig

In this paper, we use stereo vision processing techniques to detect and localise sensors used for monitoring simulated environmental events within an experimental sensor network testbed. Our sensor nodes communicate to the camera through patterns emitted by light emitting diodes (LEDs). Ultimately, we envisage the use of very low-cost, low-power, compact microcontroller-based sensing nodes that employ LED communication rather than power hungry RF to transmit data that is gathered via existing CCTV infrastructure. To facilitate our research, we have constructed a controlled environment where nodes and cameras can be deployed and potentially hazardous chemical or physical plumes can be introduced to simulate environmental pollution events in a controlled manner. In this paper we show how 3D spatial localisation of sensors becomes a straightforward task when a stereo camera rig is used rather than a more usual 2D CCTV camera

leave a trace - A People Tracking System Meets Anomaly Detection

Video surveillance always had a negative connotation, among others because of the loss of privacy and because it may not automatically increase public safety. If it was able to detect atypical (i.e. dangerous) situations in real time, autonomously and anonymously, this could change. A prerequisite for this is a reliable automatic detection of possibly dangerous situations from video data. This is done classically by object extraction and tracking. From the derived trajectories, we then want to determine dangerous situations by detecting atypical trajectories. However, due to ethical considerations it is better to develop such a system on data without people being threatened or even harmed, plus with having them know that there is such a tracking system installed. Another important point is that these situations do not occur very often in real, public CCTV areas and may be captured properly even less. In the artistic project leave a trace the tracked objects, people in an atrium of a institutional building, become actor and thus part of the installation. Visualisation in real-time allows interaction by these actors, which in turn creates many atypical interaction situations on which we can develop our situation detection. The data set has evolved over three years and hence, is huge. In this article we describe the tracking system and several approaches for the detection of atypical trajectories

Feature-based calibration of distributed smart stereo camera networks

A distributed smart camera network is a collective of vision-capable devices with enough processing power to execute algorithms for collaborative vision tasks. A true 3D sensing network applies to a broad range of applications, and local stereo vision capabilities at each node offer the potential for a particularly robust implementation. A novel spatial calibration method for such a network is presented, which obtains pose estimates suitable for collaborative 3D vision in a distributed fashion using two stages of registration on robust 3D features. The method is initially described in a geometrical sense, then presented in a practical implementation using existing vision and registration algorithms. The method is designed independently of networking details, making only a few basic assumptions about the underlying networkpsilas capabilities. Experiments using both software simulations and physical devices are designed and executed to demonstrate performance

Feature-based calibration of distributed smart stereo camera networks

A distributed smart camera network is a collective of vision-capable devices with enough processing power to execute algorithms for collaborative vision tasks. A true 3D sensing network applies to a broad range of applications, and local stereo vision capabilities at each node offer the potential for a particularly robust implementation. A novel spatial calibration method for such a network is presented, which obtains pose estimates suitable for collaborative 3D vision in a distributed fashion using two stages of registration on robust 3D features. The method is first described in a general, modular sense, assuming some ideal vision and registration algorithms. Then, existing algorithms are selected for a practical implementation. The method is designed independently of networking details, making only a few basic assumptions about the underlying network\u27s capabilities. Experiments using both software simulations and physical devices are designed and executed to demonstrate performance

An automatic calibration method for stereo-based 3D distributed smart camera networks

Stereo-based 3D distributed smart camera networks are useful in a broad range of applications. Knowledge of the relative locations and orientations of nodes in the network is an essential prerequisite for true 3D sensing. A novel spatial calibration method for a network of pre-calibrated stereo smart cameras is presented, which obtains pose estimates suitable for collaborative 3D vision in a distributed fashion using two stages of registration on robust 3D point sets. The method is initially described in a geometrical sense, then presented in a practical implementation using existing vision and registration algorithms. Experiments using both software simulations and physical devices are designed and executed to demonstrate performance

Co-operative surveillance cameras for high quality face acquisition in a real-time door monitoring system

The increasing number of CCTV cameras in use poses a problem of information overloading for end users. Smart technologies are used in video surveillance to automatically analyze and detect events of interest in real-time, through 2D and 3D video processing techniques called video analytics. This paper presents a smart surveillance stereo vision system for real-time intelligent door access monitoring. The system uses two IP cameras in a stereo configuration and a pan-tilt-zoom (PTZ) camera, to obtain real-time localised, high quality images of any triggering events