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The seafloor high-definition camera (CamHD) installed on the Ocean Observatories Initiative (OOI) Cabled Array (CA) provides real-time video of the Mushroom vent at the ASHES hydrothermal field in the Axial Volcano caldera on the Juan de Fuca spreading zone (Figure 1). CamHD performs a pre-programmed 13-minute motion sequence every 3 hours. The video captured during this sequence is stored as a 13GB...
The Ocean Observatories Initiative (OOI) has a SubC 1Cam high-definition video camera (CAMHD) delivering real-time data since August 2015 from inside the caldera of Axial Seamount volcano, approximately 450 kilometers off the coast of Washington. These data are archived on the OOI's raw data repository at Rutgers University and are publicly available for download via the Apache HTTP Server endpoint...
This paper describes the application of convolutional neural networks (CNNs) to the identification and classification of ten classes of benthic macrofauna in high-resolution photomosaics captured on the Pacific continental shelf by an ROV. Each photomosaic was previously hand-annotated with the location and classification of each animal, providing a training set for the machine learning algorithms...
The most scientifically diverse and technologically advanced component of the National Science Foundations' $386M investment in the Ocean Observatories Initiative (OOI), involves 900 kilometers of high power and bandwidth electro-optical cable extending from Pacific City, OR, across active portions of the Juan de Fuca tectonic plate and up into the overlying ocean. Completed on time and under budget...
The Ocean Observatories Initiative's (OOI) Cabled Array (CA) is delivering high-definition video data since August 2015 via fiber optic cable from a statically positioned SubC 1Cam HD (CAMHD) video camera, deployed at the Mushroom hydrothermal vent in the Axial Seamount Hydrothermal Expeditions (ASHES) Field off the coast of Oregon (lat 45° 56.0186′N, long 130° 00.8185′W, depth 1,542 m). Over 20 TB...
The introduction of low-cost RGB-depth (RGB-D) sensors have led to a diversity of algorithms for robust 3D scene reconstruction under controlled settings, but the underwater realization of such algorithms has been hampered by the constrained performance of most RGB-D sensors in water. We explore the possibility of fusing a point cloud generated from a high-frequency, mechanically scanned 3D imaging...
This paper describes Smartpig, an algorithm for the iterative mosaicking of images of a planar surface using a unique parameterization which decomposes inter-image projective warps into camera intrinsics, fronto-parallel projections, and inter-image similarities. The constraints resulting from the inter-image alignments within an image set are stored in an undirected graph structure allowing efficient...
This paper introduces the OpenCV-FFI software package, which exposes datatypes and functions from the OpenCV computer vision library into the Ruby programming language. OpenCV-FFI uses the foreign function interface (FFI) to produce a Ruby API which mirrors the OpenCV C API; further layers of complexity are then built on that core API. Example code and benchmarking results show the effectiveness of...
RANSAC has become an essential tool for the robust estimation of inter-image geometries using point correspondences. Due to its randomized nature, RANSAC becomes inefficient for large numbers of incorrect matches. This paper presents four methods for utilizing prior geometric information when estimating the homography which register a pair of near-nadir aerial images. In this case the initial geometric...
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