Structure and motion in urban environments using upright panoramas

Image-based modeling of urban environments is a key component of enabling outdoor, vision-based augmented reality applications. The images used for modeling may come from off-line efforts, or online user contributions. Panoramas have been used extensively in mapping cities and can be captured quickly by an end-user with a mobile phone. In this paper, we describe and evaluate a reconstruction pipeline for upright panoramas taken in an urban environment. We first describe how panoramas can be aligned to a common vertical orientation using vertical vanishing point detection, which we show to be robust for a range of inputs. The orientation sensors in modern cameras can also be used to correct the vertical orientation. Secondly, we introduce a pose estimation algorithm, which uses knowledge of a common vertical orientation as a simplifying constraint. This procedure is shown to reduce pose estimation error in comparison with the state of the art. Finally, we evaluate our reconstruction pipeline with several real-world examples.