Real-time multiple vehicle detection and tracking from a moving vehicle

Abstract

Abstract.A real-time vision system has been developed that analyzes color videos taken from a forward-looking video camera in a car driving on a highway. The system uses a combination of color, edge, and motion information to recognize and track the road boundaries, lane markings and other vehicles on the road. Cars are recognized by matching templates that are cropped from the input data online and by detecting highway scene features and evaluating how they relate to each other. Cars are also detected by temporal differencing and by tracking motion parameters that are typical for cars. The system recognizes and tracks road boundaries and lane markings using a recursive least-squares filter. Experimental results demonstrate robust, real-time car detection and tracking over thousands of image frames. The data includes video taken under difficult visibility conditions.

A Review on Vehicular Monitoring and Tracking

“…With the aim of accident severity and reducing injury, pre-crash sensing is becoming an area of active research among automotive manufacturers, suppliers and universities [7][8] [9]. Developing on-board automotive driver assistance systems aiming to alert a driver about possible collision and driving environments with other vehicles has attracted a lot of attention.…”

“…Vehicle accident statistics clarify that the main threats a driver is facing are from other vehicles. Consequently, developing on-board automotive driver assistance systems aiming to alert a driver about driving environments, and possible collision with other vehicles has attracted a lot of attention [7]. In these systems, robust and reliable vehicle detection is the first step -a successful vehicle detection algorithm will pave the way for vehicle tracking, vehicle recognition, and collision avoidance.…”

FaceMouse: A Human-Computer Interface for Tetraplegic People

“…It has been demonstrated [8,15] that the features that better exhibit these characteristics are those represented by convex shapes and the only convex shape easily visible on human face is the nose tip. Assuming light conditions constant between two consecutive frames, normalized cross correlation [16,17] can be exploited to perform at time t the template matching with respect to the tem- Several improvements have been introduced to increase the reliability and robustness of the system. First, the normalized cross-correlation is thresholded to retain only "sufficiently good" matches.…”

A new vehicle detection method

“…Appearance-based methods include pattern classification system between vehicle and non vehicle. There are a many works [15][16] [17] tackling realtime on-road vehicle detection problem. All the papers used monocular cameras and have realtime constraints.…”

“…All the papers used monocular cameras and have realtime constraints. [15] used horizontal and vertical edges (Knowledge-based methods) in HG step. The selected regions at HG step are matched with predefined template in HV step.…”