Detecting Path Intersections in Panoramic Video

Abstract

Given panoramic video taken along a self-intersecting path, we present a method for detecting the intersection points. This allows “virtual tours” to be synthesized by splicing the panoramic video at the intersection points. Spatial intersections are detected by finding the best-matching panoramic images from a number of nearby candidates. Each panoramic image is segmented into horizontal strips. Each strip is averaged in the vertical direction. The Fourier coefficients of the resulting 1-D data capture the rotation-invariant horizontal texture of each panoramic image. The distance between two panoramic images is calculated as the sum of the distances between their strip texture pairs at the same row positions. The intersection is chosen as the two candidate panoramic images that have the minimum distance.