Tracking and counting vehicles in traffic video sequences using particle filtering

Abstract

This paper presents a new method to track and count vehicles in video traffic sequences. The proposed method uses image processing, particle filtering, and motion coherence to group particles in videos, forming convex shapes that are analyzed for potential vehicles. This analysis takes into consideration the convex shape of the objects and background information to merge or split the groupings. After a vehicle is identified, it is tracked using the similarity of color histograms on windows centered at the particle locations.