Integrating Dashcam Views Through Inter-Video Mapping

In this paper, an inter-video mapping approach is proposed to integrate video footages from two dashcams installed on a preceding and its following vehicle to provide the illusion that the driver of the following vehicle can see-through the preceding one. The key challenge is to adapt the perspectives of the two videos based on a small number of common features since a large portion of the common region in the video captured by the following vehicle is occluded by the preceding one. Inspired by the observation that images with the most similar viewpoints yield dense and high-quality matches, the proposed inter-video mapping estimates spatially-varying motions across the two videos utilizing images of very similar contents. Specifically, we estimate frame-to-frame motions of each two consecutive images and incrementally add new views to form long-range motion representation. On the other hand, we dynamically infer spatial-varying motions across the two videos that propagated from local feature correspondences to trajectories. In this way, the observed perspective discrepancy between the two videos can be well approximated by our motion estimation. Once the inter-video mapping is established, the correspondences can be updated incrementally, so the proposed method is suitable for on-line applications. Experiments with real-world challenging videos demonstrate the effectiveness of our approach.