An automated event detection and classification system for abyssal time-series images of Station M, NE Pacific

Abstract

The time-study data collected at the Station M site off the coast of central California includes high quality still-frame images taken in 1-hour time-lapse increments. The approximately 67,000 time-lapse images collected would take an unfeasible amount of time to fully analyze manually, and therefore would benefit from automated analysis. Towards this end, this work is an aid in the significant effort to analyze megafaunal activity and sedimentation events using an adapted version of the Automated Video Event Detection and Classification System (AVEDac) formerly designed by MBARI to analyze video collected from MBARI's remotely operated underwater vehicles (ROVs) video. This paper describes, in general, the automated system that will aid in the abundance and distribution studies of animals at the Station M site.