Video

MBARI deploys video cameras on many scientific platforms. Much of this video is high quality, from High Definition cameras on ROVs and AUVs, and is used for both qualitative observations and quantitative measurements. The video is curated and annotated by trained professional staff, and the resulting annotations and measurements stored in databases. Other video and still imagery is collected using consumer- or professional-grade cameras for science or operations.

VARS: MBARI video is curated using the Video Annotation and Reference System (VARS), a software interface and database system that provides tools for describing, cataloging, retrieving and viewing the visual, descriptive, and quantitative data associated with MBARI’s deep-sea video archives. The VARS system software was made available to users outside of MBARI in November 2005. MBARI continually updates and releases improvements to VARS. Researchers and institutions can use VARS for cataloging and analyzing large or complex observation data sets. The software is available as open source code that can be adapted and improved for specific research needs.

Video analysis at MBARI: The database of deep-sea observations that have been recorded by MBARI remotely operated vehicles (ROVs) during 25+ years of operation, and associated software system, VARS, represents MBARI collective knowledge and serves as an investigative tool that facilitates deep-sea research publications as well as technical, agency, educational, and outreach projects. From this unique dataset, MBARI’s video annotation team has developed the Deep-Sea Guide (DSG). The DSG is a web-based system that allows for the correlation of visual, descriptive, and observational data with environmental data from multiple sources by providing tools for searching, identifying, and examining occurrence data (e.g., depth, time, abundance) for biological, geological, and experimental observations.

AVED: MBARI has developed an automated system for detecting marine organisms visible in the videos. Video frames are processed with a selective attention algorithm; candidate objects of interest are tracked across video frames. Objects tracked successfully over several frames are labeled as potentially “interesting” and marked in the video frames. The objective of the system is to enhance the productivity of human video annotators and/or cue a subsequent object classification module by marking candidate objects. As part of this system, MBARI is exploring state of the art object classification systems and machine learning, to enable automated video analysis.

Technology

Solving challenges
Taking the laboratory into the ocean
In Situ Ultraviolet Spectrophotometer
Midwater Respirometer System
Mobile flow cytometer
Enabling targeted sampling
Automated Video Event Detection
Gulper autonomous underwater vehicle
Advancing a persistent presence
Aerostat hotspot
Benthic event detectors
Benthic rover
Fault Prognostication
Long-range autonomous underwater vehicle Tethys
Marine “soundscape” for passive acoustic monitoring
Monterey Ocean-Bottom Broadband Seismometer
Shark Café camera
Vehicle Persistence
Wave Glider-based communications hotspot
Emerging and current tools
Communications
Aerostat hotspot
Wave Glider-based communications hotspot
Data management
Oceanographic Decision Support System
Spatial Temporal Oceanographic Query System (STOQS) Data
Video Annotation and Reference System
Instruments
Apex profiling floats
Benthic event detectors
Deep particle image velocimetry
Environmental Sample Processor
How the ESP Works
Genomic sensors
ESP Web Portal
The ESP in the news
Investigations of imaging for midwater autonomous platforms
Lagrangian sediment traps
Laser Raman Spectroscopy
Midwater Respirometer System
Mobile flow cytometer
Smart underwater connector
Power
Wave-Power Buoy
Vehicle technology
Benthic Rover
Gulper autonomous underwater vehicle
Imaging autonomous underwater vehicle
In Situ Ultraviolet Spectrophotometer
Seafloor mapping AUV
Long-range autonomous underwater vehicle Tethys
Mini remotely operated vehicle
ROV Doc Ricketts
ROV Ventana
Video
Automated Video Event Detection
Deep learning
SeeStar Imaging System
Shark Café camera
Video Annotation and Reference System
Technology publications
Technology transfer