Conventional neural networks have been demonstrated to be a powerful framework for
background subtraction in video acquired by static cameras. Indeed, the well-known Self …

Computer vision applications based on videos often require the detection of moving objects
in their first step. Background subtraction is then applied in order to separate the background …

For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …

It is important for marine scientists and conservationists to frequently estimate the relative
abundance of fish species in their habitats and monitor changes in their populations. As …

There is a need for automatic systems that can reliably detect, track and classify fish and
other marine species in underwater videos without human intervention. Conventional …

It is interesting to develop effective fish sampling techniques using underwater videos and
image processing to automatically estimate and consequently monitor the fish biomass and …

Background modeling and foreground detection are important steps in video processing
used to detect robustly moving objects in challenging environments. This requires effective …

Background modeling has emerged as a popular foreground detection technique for various
applications in video surveillance. Background modeling methods have become increasing …

Computer vision and image processing approaches for automatic underwater fish detection
are gaining attention of marine scientists as quicker and low-cost methods for estimating fish …

In this paper we present an approach for segmenting objects in videos taken in complex
scenes with multiple and different targets. The method does not make any specific …