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This article addresses the problem of near real time video analysis of a maritime scene using a (moving) airborne RGB video camera in the goal of detecting and eventually recognizing a target maritime vessel. This is a very challenging problem mainly due to the high level of uncertainty of a maritime scene including a dynamic and noisy background, camera's and target's motions, and broad variability...
In this paper, an efficient unsupervised approach for extracting objects from maritime background using solely still video images is proposed. Its main idea is that maritime background (sea) has the main particularity of absorbing only hot light frequencies (red and green), while an object has not this property. Therefore if a timely vector of class features is considered, then two distinct statistical...
This article is concerned with on-line counting of harmful insects of certain species in videos in the framework of in situ video-surveillance that aims at the early detection of prominent pest attacks in greenhouse crops. The video-processing challenges that need to be coped with concern mainly the low spatial resolution and color contrast of the objects of interest in the videos, the outdoor issues...
We describe a novel automatic approach for vesicle trafficking analysis in 3D+T videomicroscopy. Tracking individually objects in time in 3D+T videomicroscopy is known to be a very tedious job and leads generally to unreliable results. So instead, our method proceeds by first identifying trafficking regions in the 3D volume and next analysing at them the vesicle trafficking. The latter is viewed as...
We describe a novel automatic approach for vesicle trafficking analysis in 3D+T videomicroscopy. Tracking individually objects in time in 3D+T videomicroscopy is known to be a very tedious job and leads generally to unreliable results. So instead, our method proceeds by first identifying trafficking regions in the 3D volume and next analysing at them the vesicle trafficking. The latter is viewed as...
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