Vehicle detection and Attribute based search of vehicles in video surveillance system

Vehicle detection is important in traffic monitoring and control. Traditional methods which are based on license plate recognition or vehicle classification which may not be effective for low resolution cameras or when number plate is not available. Also, Vehicle detection in urban scenarios, based on traditional methods like background subtraction fails. To overcome this limitation, this paper present co-training based approach for vehicle detection[1]. Feature selected for detection is haar. Based on haar-training classifier is trained and adaboost is used to get strong classifier. After detection of vehicle, next step is to search for particular vehicles based on its description. Searching of suspicious vehicles is important in criminal investigation. Search framework allows the user to search for vehicles based on attributes such as color, date and time, speed, direction in which vehicle is travelling. Attribute based Vehicle search includes example query "Search for yellow cars moving into horizontal direction from 5.30pm to 8pm". Output of search query is reduced size version of detected vehicles are displayed.