[9/21~ Conference] Frequency Biology Project to Present Research and Exhibit at OCEANS 2026 Monterey
Susumu Takatsuka et al. of the Frequency Biology Project will present a poster at OCEANS 2026 on their research into plankton behavior analysis using Event-based Vision Sensors (EVS). A demonstration of a plankton analysis technology developed based on this research will also be featured at the conference exhibition booth.
Title: Advancing Marine Particle and Organism Observation Using Event-based Vision Sensors (EVS)
Date: September 21～24, 2026
Venue: Monterey Conference Center
URL: https://monterey26.oceansconference.org/
Abstract
Recent advances have expanded the use of event cameras (Event-based Vision: EVS, DVS, Event camera) in biological observation. EVS is a sensor that asynchronously outputs only brightness changes at each pixel. Compared with frame-based sensors (FBS), which acquire all pixels at fixed intervals, EVS offers high temporal resolution, low data rates, and reduced sensitivity to motion blur and exposure saturation. These properties make EVS suitable for capturing fast, non-stationary biological motion and the behavior of small particles. Applications have been reported in wildlife, insect, fish, and bat monitoring, as well as high-speed motion analysis. In marine science, EVS-based plankton observation has also shown promise.
Microscopic organisms such as plankton and larvae are known to exhibit rapid movements of their swimming organs. With conventional frame cameras, particle tracking may be possible, but detailed measurement of the motion characteristics of individual particles is difficult. In contrast, EVS can not only count particles accurately but also capture periodic shape changes associated with swimming motion at high speed and extract motional features through frequency analysis. This enables classification of particles into active particles, which exhibit swimming motion, and passive particles, which do not. Such classification has often relied on post-sampling observation, but EVS enables direct in situ classification without water sampling. Because organisms show characteristic motion patterns depending on size and species, analysis of multiple motional features may also enable coarse taxonomic classification. This further suggests the potential of biomass measurement without water sampling. In this study, we conducted both laboratory observations using EVS and underwater in situ observations using an EVS installed in a pressure-resistant housing, demonstrating its effectiveness as a foundational technology for advancing EVS-based observation of marine particles and organisms.
