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Computer vision has become the tool of two-dimensional image recognition and analysis, which mainly means extracting image features. But the problem of robustness and real-time property in complex scenarios makes feature extraction become a challenging task. Visual attention is an important psychological adjustment mechanism in the process of human visual information management, under the guidance...
Daily increasing underwater visual data makes automatic object detection and recognition a great demand and challenging task. In this paper, we adopt a region proposal network to accelerate underwater object detection and recognition from Faster R-CNN. This process implement detection acceleration by using convolutional networks to generate high-quality object candidates, and by sharing these networks...
An advanced and accurate census methodology that fuses acoustic and visual census of the freshwater dolphins has been successfully introduced for the Ganges river dolphins that inhabit and migrate in a long tract of the Ganges river system. In order to conduct an accurate census of the dolphins, an acoustic array system with provision to display the dolphin's real-time direction data on a GUI (Graphical...
In this paper, we try to combine Bag-of-Words (BoW) with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) together for one kind of sparse representation in the seafloor visual saliency evaluation. Properties in the water, due to the large amount of acoustic noises, sonar signals are easily polluted and interfered during image collection, and the sonar images usually diverge from...
Zooplankton are quite significant to the ocean ecosystem for stabilizing balance of the ecosystem and keeping the earth running normally. Considering the significance of zooplantkon, research about zooplankton has caught more and more attentions. And zooplankton recognition has shown great potential for science studies and mearsuring applications. However, manual recognition on zooplankton is labour-intensive...
Autonomous underwater vehicles (AUVs) often perform high-resolution survey missions. Such missions are often planned on low resolution bathymetry maps using offline coverage planning methods, e.g., using a standard lawn-mower trajectory that is adapted to the coarse-resolution representation of the terrain. We present in this paper an approach to adapt the exploration online during the mission, namely...
Robust and accurate navigation of underwater vehicles is an essential cornerstone for mission success. Integrative techniques, e.g., using inertial navigation or Doppler velocity logs (DVL), can show significant drift. Even absolute input, such as GNSS input or magnetometers, can either be biased by surrounding structures or very noisy. For good navigation performance in critical maneuvers close to...
This paper presents the last developments towards vision-based target tracking by an AUV. The main concepts behind the visual relative localization are provided and the results from a statistical analysis for the relative localization algorithm are presented. The purpose of this analysis is to ensure properness of data used to feed controllers that are responsible for governing the AUV motion. A new...
Anticipated growth of sub-sea technologies for security, infrastructure inspection, and exploration, motivates a deeper understanding of dynamics of underwater navigation in proximity to a submerged target surface. In this paper we discuss the phenomenon of a smooth, submersible micro robot with a single bottom jet that enables hovering and sliding over underwater surfaces. Such motion has applications...
Coral reefs exhibit the highest biodiversity in the ocean and are an extremely vulnerable ecosystem. Monitoring the state of the reefs is a tedious process performed by human divers which can be automated. This paper presents the use of several inexpensive drifting sensor nodes in order to reconstruct a visual mosaic of a shallow coral reef. The drifters produce geo-referenced visual data from a downward...
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