A significant issue associated with the use of video see-through head-mounted displays (VST-HMD) for augmented reality is the presence of latency between real-world images and the images displayed to the HMD. For a static scene, this latency provides no real problem, however for dynamic scenes, which arise when the HMD user moves their head, when real-world objects move, or a combination of the two, the accompanying delay may result in significant registration error. To address this issue, we present DotWarp, a novel latency reduction technique for VST-HMDs that does not rely on head motion and compensates for the delay arising from real-world object motion. The algorithm requires a two-camera setup and matches dynamic objects in both images by tracking on the faster image and warping the pixels of the slower image, with the fast and slow components being RGB and IR components, respectively, for our system. First, moving objects are extracted from the faster camera scene using a motioncompensating background subtraction algorithm and tracked using a robust correlation tracker. Then, temporal correspondence between the two camera images is computed using sensor update information and the objects' positions in the slower image are shifted to match the corresponding positions in the faster image. Finally, the gaps in the slower image left behind by the shifted objects are filled in with background pixel data from previous frames using homography from the background subtraction model. In this manner, the augmented image is more closely matched with the real-world image and the perceived registration of the camera is significantly improved, with initial results of an 81.64% reduction in registration error.