Detection and Summarization of Salient Events in Coastal Environments

Abstract

The monitoring of coastal environments is of great interest to biologists and environmental protection organizations with video cameras being the dominant sensing modality. However, it is recognized that video analysis of maritime scenes is very challenging on account of background animation (water reflections, waves) and very large field of view. We propose a practical approach to the detection of three salient events, namely boats, motor vehicles and people appearing close to the shoreline, and their subsequent summarization. Our approach consists of three fundamental steps: region-of-interest (ROI) localization by means of behavior subtraction, ROI validation by means of feature-covariance-based object recognition, and event summarization by means of video condensation. The goal is to distill hours of video data down to a few short segments containing only salient events, thus allowing human operators to expeditiously study a coastal scene. We demonstrate the effectiveness of our approach on long videos taken at Great Point, Nantucket, Massachusetts.