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Unveiling unusual or hostile events by observing manifold moving persons in a crowd is a challenging task for human
operators, especially when sitting in front of monitor walls for hours. Typically, hostile events are rare. Thus, due to
tiredness and negligence the operator may miss important events. In such situations, an automatic alarming system is
able to support the human operator. The system incorporates a processing chain consisting of (1) people tracking, (2)
event detection, (3) data retrieval, and (4) display of relevant video sequence overlaid by highlighted regions of interest.
In this paper we focus on the event detection stage of the processing chain mentioned above. In our case, the selected
event of interest is the encounter of people. Although being based on a rather simple trajectory analysis, this kind of
event embodies great practical importance because it paves the way to answer the question "who meets whom, when and
where". This, in turn, forms the basis to detect potential situations where e.g. money, weapons, drugs etc. are handed
over from one person to another in crowded environments like railway stations, airports or busy streets and places etc..
The input to the trajectory analysis comes from a multi-object video-based tracking system developed at IOSB which is
able to track multiple individuals within a crowd in real-time [1]. From this we calculate the inter-distances between all
persons on a frame-to-frame basis. We use a sequence of simple rules based on the individuals' kinematics to detect the
event mentioned above to output the frame number, the persons' IDs from the tracker and the pixel coordinates of the
meeting position. Using this information, a data retrieval system may extract the corresponding part of the recorded
video image sequence and finally allows for replaying the selected video clip with a highlighted region of interest to
attract the operator's attention for further visual inspection.
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