In this article we introduce a novel method for improving the accuracy of density reconstructions based on markers pushed forward by some available particle code.The method relies on the backward Lagrangian representation of the transported density, and it evaluates the backward flowusing the current position of point particles seen as flow markers.Compared to existing smooth particle methods with either fixed or transformed shapes, the proposed reconstruction achieves higher locality and accuracy. This is confirmed by our error analysis which shows a theoretical gain of one convergence order compared to the LTP/QTP methods introduced in [Campos Pinto, M., 2015. Towards smooth particle methods without smoothing. Journal of Scientific Computing, 65, pp.54–82], and by numerical experiments that demonstrate significative CPU gains and an improved robustness relative to the remapping period.