Temporal Structure Methods for Image-Based Change Analysis

Abstract – This paper addresses the exploitation of massive numbers of image-derived change detections. We use the term “change analysis ” to emphasize the intelligence value obtained from large numbers of change detection over long time intervals, rather than the emphasis by most researchers to date on “change detection ” methods and small numbers of change detections. Our methods emphasize local temporal descriptions of activities and include minimal spatial information about activities. Our three methods adapt and extend: (1) classic unsupervised pattern recognition operating on bag-of-words features; (2) Latent Semantic Analysis (LSA); and (3) probabilistic LSA (PLSA). These methods allow us to: (a) Detect and describe anomalou