Image-based walkthroughs from incremental and partial scene reconstructions

We present a scalable and incremental approach for creating interactive image-based walkthroughs from a dynamically growing collection of photographs of a scene. Prior approaches, such as [16], perform a global scene reconstruction as they require the knowledge of all the camera poses. These are recovered via batch processing involving pairwise image matching and structure from motion (Sfm), on collections of photographs. Both steps can become computational bottlenecks for large image collections. Instead of computing a global reconstruction and all the camera poses, our system utilizes several partial reconstructions, each of which is computed from only a small subset of overlapping images. These subsets are efficiently determined using a Bag of Words-based matching technique. Our framework easily allows an incoming stream of new photographs to be incrementally inserted into an existing reconstruction. We demonstrate that an imagebased rendering framework based on only partial scene reconstructions can be used to navigate large collections containing thousands of images without sacrificing the navigation experience. As our system is designed for incremental construction from a stream of photographs, it is well suited for processing the ever-growing photo collections.