Essay On Surveillance Cameras

In recent years, the use of surveillance systems to monitor the streets and highways attracts much attention. On the other hand, due to the large number of cameras all over a city, the memory space required, time consuming problem, and costly use of human operators has led researchers to look for ways to automate the traffic scenes understanding using surveillance cameras. Traffic scene understanding may contain detecting of anomalies such as accidents, identifying traffic levels, detection of average vehicle speed and so on. The real time traffic scene understanding has many usages; however, human operators would not be able to get information from it quickly and truly. For instance, if a driver knows the traffic level of a highway, be aware of an accident accrued in a road, or knows the average speed of vehicles in different street and roads, he can easily choose the best route and reach to his destination in minimum time or in light traffic routes. Furthermore, traffic scene understanding could be helpful in developing the smart maps. These maps are able to detect the best route with different criteria such as fastest route or nearest route.
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However, in the real world, there are many other situations where decisions are made a little harder using surveillance camera. Weather conditions such as rainy weather, dirty cameras, shadows in the image, the reflection of sunlight on surveillance cameras and different times of the day such as darkness could make the decision process harder. Very little researches have been conducted in these areas which have only been able to examine one of these special status. It is obvious that considering the normal or just one special condition will limit the use of the system and it would be impossible or along with high error to use such a system in practical terms. For example, there are several studies for traffic flow analysis at