PUB - Publikationen an der Universität Bielefeld

Abstract Given the need to describe, analyze and index large quantities of marine imagery data for exploration and monitoring activities, a range of specialized image annotation tools have been developed worldwide. Image annotation - the process of transposing objects or events represented in a video or still image to the semantic level, may involve human interactions and computer-assisted solutions. Marine image annotation software (MIAS) have enabled over 500 publications to date. We review the functioning, application trends and developments, by comparing general and advanced features of 23 different tools utilized in underwater image analysis. \{MIAS\} requiring human input are basically a graphical user interface, with a video player or image browser that recognizes a specific time code or image code, allowing to log events in a time-stamped (and/or geo-referenced) manner. \{MIAS\} differ from similar software by the capability of integrating data associated to video collection, the most simple being the position coordinates of the video recording platform. \{MIAS\} have three main characteristics: annotating events in real time, in posteriorly to annotation and interact with a database. These range from simple annotation interfaces, to full onboard data management systems, with a variety of toolboxes. Advanced packages allow to input and display of data from multiple sensors or multiple annotators via intranet or internet. Posterior human-mediated annotation often include tools for data display and image analysis, e.g. length, area, image segmentation, point count; and in a few cases the possibility of browsing and editing previous dive logs or to analyze annotation data. The interaction with a database allows the automatic integration of annotations from different surveys, repeated annotation and collaborative annotation of shared datasets, browsing and querying of data. Progress in the field of automated annotation is mostly in post processing, for stable platforms or still images. Integration into available \{MIAS\} is currently limited to semi-automated processes of pixel recognition through computer-vision modules that compile expert-based knowledge. Important topics aiding the choice of a specific software are outlined, the ideal software is discussed and future trends are presented.