The　vision-based　mobile　robot＇s　simultaneous　localisation　and　mapping　and　navigation　capability　in　dynamic　environments　are　highly　problematic　elements　of　robot　vision　applications.　The　goal　of　this　study　is　to　reconstruct　a　static　map　and　track　the　dynamic　object　for　a　camera　and　laser　scanner　system.　An　improved　automatic　calibration　is　designed　to　merge　image　and　laser　point　clouds.　Then,　the　fusion　data　is　exploited　to　detect　the　slowly　moved　object　and　reconstruct　static　map.　Tracking-by-detection　requires　the　correct　assignment　of　noisy　detection　results　to　object　trajectories.　In　the　proposed　method,　occluded　regions　are　combined　3D　motion　models　with　object　appearance　to　manage　difficulties　in　crowded　scenes.　The　proposed　method　was　validated　by　experimental　results　gathered　in　a　real　environment　and　on　publicly　available　data.