Consumer Media Capture: Time-Based Analysis and Event Clustering

fractal, clustering, photography, consumer, capture, organization, management We present an analysis of consumer media capture behavior based on timestamp metadata. We show that it is bursty and is not well described by a Poisson model. We show that it is in fact a fractal process, with fractal dimension characteristic of the capturer. We also present an algorithm for splitting consumer media into event clusters based on capture-time metadata, an algorithm for minimal labeling of such clusters, and a method for visualizing the results of such clustering on highly bursty data. We present results of the analysis on consumer photograph collections and results of the clustering using two software implementations, one for static organization and one for dynamic browsing.