2010-03-17: Computer Vision and Road Safety

Speaker: Håkan Ardö Vision@Math

To study and compare the safety of intersection, traffic scientists today typically manually monitor the intersection during several days and count how often certain events such as evasive manoeuvres occur. This is a laboursome and costly procedure. The aim of this work is to provide tools that can reduce the amount of manual labour required by using automated video analytics. Two methods for creating for such tools are presented.

The first method is a probabilistic background foreground segmentation that for each block of pixels calculate the probability that this block currently views the static background or some moving foreground object.



The second method is a multi-target tracker that uses the probabilistic background foreground segmentation to produce the trajectories of all objects in the scene. It operates online but with a few seconds delay in order to incorporate information from both past and future frames when deciding on the current state.

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Sidansvarig: Jonas.Wisbrant@cs.lth.se | 2015-11-06