1. A method for road scene understanding of vehicles in traffic, comprising capturing images of traffic with a camera coupled to a vehicle; generating a continuous model of occlusions with a continuous occlusion mode for traffic participants to enhance point track association accuracy without distinguishing between moving and static objects; applying the continuous occlusion model to handle visibility constraints in object tracks; combining the point track association and soft object track modeling to improve 3D localization accuracy; and modelling objects as translucent 3D ellipsoids whose opacity is maximum at the center and falls off towards the edges, further comprising modeling occupancy at location x corresponding to a traffic participant-centered at p as: 
 ƒ occ ( x )= L ( x;p, Σ) where L(•) is a logistic given by L ⁡ ( x ; p , Σ ) = 1 1 + e - k ⁡ ( 1 - d ⁡ ( x , p ) ) , with d(x,p)=(x−p) T Σ(x−p) being a Mahalanobis distance.