Multi-resolution Image Analysis for Vehicle Detection

Object tracking using vision technology is one of the important and complex functions in computer vision. It should become more challenge in case of there are partial occlusions and significant clutter. A mean shift procedure embedded approach for vehicle and pedestrian tracking under real road scenes is presents. A combined hue and saturation of HSI color model and local orientation information are extracted and constructed to represent the target features since it is more robust to illumination than only RGB color space. The mean shift procedure is employed to fast searching the mode of the potential object in a neighborhood of current video sequence. Meanwhile, a global motion compensation is considered for improve the robust and real-time of the tracking procedure. Some examples are investigated and used to evaluate the proposed approach. Experimental results demonstrate that the proposed approach is robust and validate in complicated real scenes.

show abstract

A Robust Vehicle Tracking Approach Using Mean Shift Procedure

Shen

Mao

et al. 2009

2009 Fifth International Conference on Information Assurance and Security

View full text Add to dashboard Cite

Multi-resolution Image Analysis for Vehicle Detection

Cited by 4 publications

References 15 publications

A Computationally Economic Novel Approach for Real-Time Moving Multi-vehicle Detection and Tracking toward Efficient Traffic Surveillance

A Computationally Economic Novel Approach for Real-Time Moving Multi-vehicle Detection and Tracking toward Efficient Traffic Surveillance

Vision Based Navigation System of Intelligent Vehicles: A Robust Object Tracking Approach

A Robust Vehicle Tracking Approach Using Mean Shift Procedure

Contact Info

Product

Resources

About