The multitude of cameras constantly present nowadays redefined the meaning of capturing an event and the meaning of sharing this event with others. The images are frequently uploaded to a common platform, and the image-navigation challenge naturally arises. We introduce RingIt - a spectral technique for recovering the spatial order of a set of still images capturing an event taken by a group of people situated around the event. We assume a nearly instantaneous event, e.g., an interesting moment in a performance captured by the digital cameras and smartphones of the surrounding crowd. The ordering method extracts the K-nearest neighbors (KNN) of each image from a rough all-pairs dissimilarity estimate. The KNN dissimilarities are refined to form a sparse Weighted Laplacian, and a spectral analysis then yields a ring angle for each image. The spatial order is recovered by sorting the obtained ring angles. The ordering of the unorganized set of images allows for a sequential display of the captured object. We demonstrate our technique on a number of sets capturing momentary events, where the images were acquired with low-quality consumer-cameras by a group of people positioned around the event.
@article{elor2015ringit,
author = {Hadar Averbuch-Elor and Daniel Cohen-Or},
title = {RingIt: Ring-Ordering Casual Photos of a Temporal Event},
journal = {ACM Transactions on Graphics},
volume = {34},
number = {3},
article = {33},
year = 2015,
}
To appear later...
This work supported by the Israel Science Foundation.
Last update to the page: February 20, 2015.