RingIt: Ring-Ordering Casual Photos of a Temporal Event

The multitude of cameras constantly present nowadays redefines 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, such as 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.