Street Slide: Browsing Street Level Imagery

Systems such as Google Street View and Bing Maps Streetside enable users to virtually visit cities by navigating between immersive 360° panoramas, or bubbles. The discrete moves from bubble to bubble enabled in these systems do not provide a good visual sense of a larger aggregate such as a whole city block. Multi-perspective "strip" panoramas can provide a visual summary of a city street but lack the full realism of immersive panoramas.

We present Street Slide, which combines the best aspects of the immersive nature of bubbles with the overview provided by multiperspective strip panoramas. We demonstrate a seamless transition between bubbles and multi-perspective panoramas. We also present a dynamic construction of the panoramas which overcomes many of the limitations of previous systems. As the user slides sideways, the multi-perspective panorama is constructed and rendered dynamically to simulate either a perspective or hyper-perspective view. This provides a strong sense of parallax, which adds to the immersion. We call this form of sliding sideways while looking at a street façade a street slide. Finally we integrate annotations and a mini-map within the user interface to provide geographic information as well additional affordances for navigation. We demonstrate our Street Slide system on a series of intersecting streets in an urban setting. We report the results of a user study, which shows that visual searching is greatly enhanced with the Street Slide interface over existing systems from Google and Bing.

Kopf-sg10.pdf
PDF file

In  ACM Transactions on Graphics (Proceedings of SIGGRAPH 2010)

Publisher  Association for Computing Machinery, Inc.
Copyright © 2010 by the Association for Computing Machinery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212) 869-0481, or permissions@acm.org. The definitive version of this paper can be found at ACM’s Digital Library --http://www.acm.org/dl/.

Details

TypeArticle
URLhttp://research.microsoft.com/en-us/um/people/kopf/street_slide/index.html
Volume29
Number4
> Publications > Street Slide: Browsing Street Level Imagery