This paper addresses the dim target tracking problem with respect to the multi-frame detection (MFD). Generally, the MFD strategy implicitly merges the tracking stage into its framework, by which the estimated target trajectory can be simultaneously returned when a target is declared. However, due to the batch processing manner of MFD, such products, essentially, are short state sequences in time series (or short track segments), rather than the wanted continuous long target trajectories. In this paper, a novel target detection and tracking scheme, i.e., the multi-frame detection and tracking (MFDT) is proposed, wherein a specially designed tracker is assigned after the MFD as a supplement, which can combine and fuse such short track segments into continuous, accurate target trajectory. By using some reasonable assumptions, an optimal filtering algorithm for this fusion problem is also derived in this paper. Numerical results show that the proposed MFDT method can effectively improve the tracking performance both compared with the classical tracking and the only MFD method.