CrowdCam: Instantaneous Navigation of Crowd Images Using Angled Graph

• Main Authors: Arpa, Aydin (Contributor), Ballan, Luca (Author), Sukthankar, Rahul (Author), Taubin, Gabriel (Author), Pollefeys, Marc (Author), Raskar, Ramesh (Contributor)
• Other Authors: Massachusetts Institute of Technology. Media Laboratory (Contributor), Program in Media Arts and Sciences (Massachusetts Institute of Technology) (Contributor)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers (IEEE), 2014-12-23T15:56:31Z.
• Subjects: Article
• Online Access: Get fulltext

We present a near real-time algorithm for interactively exploring a collectively captured moment without explicit 3D reconstruction. Our system favors immediacy and local coherency to global consistency. It is common to represent photos as vertices of a weighted graph, where edge weights measure similarity or distance between pairs of photos. We introduce Angled Graphs as a new data structure to organize collections of photos in a way that enables the construction of visually smooth paths. Weighted angled graphs extend weighted graphs with angles and angle weights which penalize turning along paths. As a result, locally straight paths can be computed by specifying a photo and a direction. The weighted angled graphs of photos used in this paper can be regarded as the result of discretizing the Riemannian geometry of the high dimensional manifold of all possible photos. Ultimately, our system enables everyday people to take advantage of each others' perspectives in order to create on-the-spot spatiotemporal visual experiences similar to the popular bullet-time sequence. We believe that this type of application will greatly enhance shared human experiences spanning from events as personal as parents watching their children's football game to highly publicized red carpet galas.
Swiss National Science Foundation
European Commission (ERC grant #210806 4DVideo, 7th Framework Programme (FP7/2007- 2013))